 Okay, so good morning, good afternoon, good evening, and welcome to today's webinar, virtual training on the SDG indicator two for one. My name is Stefania Bacci, I am Italian. I am a statistician working in the statistics division FAO since 2008. I started working the SDG two for one team in early 2020. This is the second round of the virtual trainings on the SDG two for one, we have indeed already carried out three very successful virtual trainings in 2020. And this year, we would like to replicate the experience. And that's why we're having other five years. So we have carried out the first of 2021, early this month with the African region, and you are now the second group of countries. We have today a record of time zones, at least for our experience because in Cook Island it is still yesterday actually it is 5pm of the 27th of June. So by the way, Apologize and thanks for joining on Sunday. And here in Italy it's 5am. So we have really 12 hours difference in our meeting really incredible. I must admit it has not be easy to find the proper time for all countries present today. And this is the best we could do. So before starting, let me thank deeply our colleague from the FAO Regional Office of Bangkok, Mr. Tomara Jitendra Singh, who has been precious in this coordination phase. So now let me give the floor to Aspandar who is the key person for this training for the official welcome address over to you Aspandar. So thank you very much, Stefania. And good morning and to everyone and a very warm welcome to all of you to this first day of the virtual training on SDG 241 amid coronavirus pandemic. This is the third in the series of the three virtual trainings in 2021 of which the first two have already been successfully organized in the last couple of months. We are forcing to other virtual trainings later down this year. For this training we are expected to be joined by approximately 120 esteemed officials from across Asia with representatives from 18 countries. So some of which got trained on the indicator in the recent past or have contributed to the indicator methodology or what part of the indicator testing phase. My name is Abab Aspandar Khan and I work as an economist with statistics division of FAO at its head water in in Rome and will be your leading resource person for the four days virtual training on SDG 241. I'm joining Stefania already introduced herself. I'm joined by her she is the one behind making the all the organizational arrangements for this training, and will be a will be playing a key role of moderator during the course of the next four days. I hope that this virtual training will be a great opportunity for all of you to enhance your understanding about the conceptual and methodological aspects of SDG indicator 2.4.1 and its policy use once it's gets implemented. It will be interactive as we gradually in a phase manner cover the different aspects of the indicator that is its conceptual and methodological basis scope coverage periodicity the data collection analysis tools and the processes and protocols and mechanisms for reporting it back to FAO. As we move along, we will take several breaks for questions and discussions and trying to answer and accommodate your questions that you may have. Let me extend my thanks to the regional statistician. Thanks from FAO regional and country offices, especially Thomas Stefania already thanked him for his rigorous coordination in making this training happen. But in any case, let me thank everyone for their gracious support in in in making the organizational aspects of this training successful. We really appreciate it. At least we would like to express our gratitude and profound appreciations to the respected participants who have made room in their busy work schedule to attend this training in these extraordinary circumstances. We're expecting an active participation and constructive discussion throughout the course of this training. So thank you very much once again, with this brief introduction I will now leave the floor to Stefania for her to walk us through some important housekeeping rules that will go on this training so Stefania the floor is yours. Thank you very much. So let me share again my screen. Before maybe I left the share screen a little bit too much. Okay. Okay, sure. Okay, you should see now again. My screen. Okay, so, as I said, let me immediately give you some quickly quickly some few instructions that were already actually listed in the concept notes but maybe it's part of my life. Again, if you're so, preferably use a computer it's a personal computer or a laptop and not a mobile phone or a tablet. This is because the context sometime could be heavy to follow. So it's important to have a big screen. And also that you are comfortable in a silent place with no background noise please or echo. And you have also a clear vision of your monitor and please turn off all the sounds notification so Skype, what's up emails, whatever. If you have connectivity issues, our boy voice breaks or the video phrase close all the other application that you might have open on your computer. And if it doesn't work also maybe check through your house or your office whatever you have, you are, if you can switch off some devices. So you can access zoom from all devices via web browser or via the application, but we really say that downloaded the app is strongly recommended for a better experience. Also zoom regularly provides a new version of the application or the application so it's strongly recommended to check for updates to ensure that all the new features work on your computer and also to enhance the security of the application. So to do so, please go open the app and click on your profile picture of the top right of the window and then you check for updates. For a better sound quality please do not use if possible your built-in computer microphone by use a USB headset with integrated microphone or white earphone and microphone. If several participants use one unique microphone, please make sure we speaking is close to the microphone. For future use sessions will be recorded and uploaded online on the SDG webpage. So in case you don't want to show your face your research, please keep your camera off, even if you are talking before going into a few rules. I know that this training has been organized in a webinar mode. So we have two lead representatives for countries that are more than welcome to intervene during the discussion. And these people are visible as finalists so you can see the list. And that we have a couple of countries, so Mongolia and Laos that did not nominate those two lead representatives yet. So please, the representatives from the nominated from these countries can you please write me in the chat so that I can promote those two people per country as finalists. So for the two lead representatives, please follow the meeting in mute mode and click the mute button only when speaking on when or when you're giving the floor. Because today we are more than 100 participants in total, and of it can help to have noises in the background that disturbs the trainers. So we kindly ask to have also the camera switch off for not overloading the internet bandwidth, and you can switch the camera on, of course when speaking, the two icons are visible here on the bottom left of the zoom interface. And for the other participants is not so not for the panelist, you don't have the possibility to unmute or to turn on the camera, but the host can allow you to do it. So this will be granted with the little exceptions, exceptions, we apologize but this is needful for this kind of meeting with such a big number of participants. So I have a question that cannot be asked in the question and answer section, and you are not among the panelist. Please ask for the floor and we will evaluate case by case, if allowing this exception. For both the panelist and the participants at any time during the webinar, you'll have the opportunity to submit your questions to today's presenters. So to do so just type your question in the Q&A section. Do not use the chat box please to ask questions. So you can directly write the question or you can mention that you have one, and then you wait for the SDG241 team to give you the floor. In that case you can unmute yourself, have your video on, unless of course you don't want to, you speak loud please and close to the microphone stating your country first and then your questions. Speak concisely, slowly, clearly, and then when you are finished you can mute yourself back and switch off the camera. You can also raise the hand virtually for requesting the floor. So look for this symbol so that it's the raise hand function. And if you don't have the icon in the bottom bar you can find it in the participants menu. As time allows of course the presenter will address as many questions they can during the Q&A section at the end of the presentation. So the floor will be passed to participants based on the order that appear on my screen. And to the extent possible of course. And if many questions are asked that we will answer them by email. So anyway please be assured that we'll reply to all of them. So we kindly ask to renominate yourself. So please ensure that your name, the name of your country appears in the name box. So to do this, please click on the dots appearing on the right hand corner of your image box and rename and insert your country and then your last name please. From time to time the SDG 241 team will ask questions as sort of quizzes through the poll function. Please so don't hesitate to ask clarification if something is not clear. Since you will be asked to really reply to all questions. Finally, whatever issue you have, please write me, you can use the private chat so you can change it easily in the general chat you just need to change the recipient name to all panelists all to Stefano Bacci which is myself. And I will be happy to help for any kind of doubts question or technical matters that you have. Before starting let me say that the link of the recordings of the entire virtual training will be shared with you after the third day. And we will be sending also certificates to all participants that will attend the three days. So we apologize but we cannot send them certificate to those who will attend only one or two days. We will share the in advance all the power points, but we will share them again with you after the third day together with many other supporting documents. So that's all for now hope everything was clear case not you know I am available through the chat. So let me stop sharing the presentation and let me share with you the agenda. Okay, sorry. So share the Excel. Okay. So today we started the agenda for this trainings. So today, we started, we start to be a very intense they we are going to learn everything about the SDG to for one, specifically specifically as one yard with introduced as the SDG to for one, and it's three dimensions so the economic the environmental and the social dimensions. And then we will start presenting the one by one all the 11 sub indicators. We plan to have all the economic dimension completed by today. So covering the first piece of indicators. And after each sub indicator presented and explained by a spam yard, we will give you an exercise. You have already actually received in the edition email. And we will reason together on how to calculate is each sub indicator. So moreover, we will be launching as I said also some quizzes to assess if you have adequately acquired knowledge trust and during the presentation. We will do also. I mean, the, the, the idea is to have also this kind of organization also for the next three days so indicator and then exercise and then quits. And of course we will take also 30 minutes may break, or maybe a little bit less so we will see during the training. Tomorrow we will continue with the remaining sub indicators. I think for sure we will try, we will manage to cover all five of the environmental dimension, and maybe one of the social, let's see. Then we will have a colleague of the Agris team that will present the Agris and 50 by 2030 initiative on the third day. We will finish presenting the social dimension if we need to, of course. And we will talk about the data collection tools. So meaning the questionnaires, and we will talk about the alternative data sources. And then we will give, and then I will present also the findings of the first dispatch carried out last year so the first comprehensive patch. And the last session will be dedicated to the file set and a colleague from our team we present so this presentation. The last day, we will open the day with a presentation from a span year showing the short, medium and long term expectations for two for one. And then a colleague from statistics Indonesia will present their experiences so it will be very interesting. And finally, we will open the discussion to all countries. So especially on this fourth day. The lead representative will be requested to speak up and share the experience and concern on the SDG to for one data collection and calculation. So it will be a very important session for us because we will be listening to you. So if you don't have any question, let's start immediately so I give again the floor to us from there, who will present the as the 20, we will start the presentations on the SDG to for one. So, as one yard over to you again. Thank you very much Stefania so now let me share my screen with with all of you. Can you please confirm if you can see my presentation. Yes. Okay perfect. So, okay. So let's, let's discuss the core objectives that we want to achieve during this training. So first and foremost, as Stefania mentioned, I will walk you through the SDG to for one conceptual and methodological analysis is compilation and interpretation. We will then cover the data tools and instruments developed both for collecting and reporting data on the indicator. Here you will get to know about the survey questionnaire and related documents. We will also get to know about SDG to for one in the context of agris survey and 50 by 2030 initiative. Mind you, these are two flagship projects by FAO that are getting implemented in collaboration with World Bank and if hard, however, we will discuss more about it in in a dedicated session. We will also cover the FAO data collection questionnaire as an instrument used by us to collect data from from the member states. We will also discuss with you the, sorry, the data gaps and your concrete plans in the short, medium and long term to collect data on the indicator in order to bridge those gaps and as well as final reporting to FAO. And our all aim of this training is to unite and assemble key stakeholders at the country level. By this, I mean those people or officials who are responsible for collecting and reporting data that is representatives from the National Statistical Office. And also those responsible for then using that data for evidence based policies and decisions at the national or sub national level. That is the representative from Ministry of Agriculture and other relevant institutions and organizations. So to contextualize at FAO, we develop global public goods that is methodologies standards and classifications and coordination consultation and close partnership with the stakeholder at all levels. So from historical perspective in early 2016, the FAO strategic program on sustainable agriculture and global strategy to improve agriculture and rural statistics joint forces to develop the pioneer methodology for the then tier three SDG indicator 2.4.1 to measure progress towards target 2.4. As many of you may know defining and measuring sustainable agriculture, which is a multi dimensional concept is challenging as it is complex country specifics specific and thus despite several attempts in the past 50 years since 1970s has never been done before. Given the multi dimensionality of the sustainability concept. So that FAO initiated a global discussion to deliberate the fundamental questions that is what sustainability means in the context of agriculture. What are its fundamental building blocks. What are the economic, social and environmental factors that affect and are in turn affected by sustainability and agriculture. Inter-temporal and inter spatial way. You will find out in the course of this training that the methodology that we have developed to measure and monitor SDG 2.4.1 involve simple straightforward rules to arrive at sustainability assessments of the country once the data has been collected, cleaned, processed and analyzed. The approved and endorse methodology of SDG 2.4.1 is a result of long participatory and concentrated process that involve discussion with and contribution of thematic and subject matter experts, statisticians, policymakers and researchers from country institutions, that is national statistical offices and ministry of agriculture, obviously, but as well international organizations, civil society, private sector and academia on the very issue I mentioned earlier. The reason behind us involving all these key stakeholders with diverse background and experiences was to make this indicator owned by everyone, especially countries. The current methodology of SDG 2.4.1 that we will cover in detail, embodies the following principles that is its universal policy relevant and practical. This was to ensure sustainability of the indicator monitoring over time at the country level. Now, let us go to the methodology itself SDG 2.0 hunger has five targets. The target that we are interested in today is target 2.4, which is written in detail here. As you can see, like many other SDG targets, this target is a very complex one. We highlighted in red some of the key aspects that needs to be captured as we try to measure progress towards this target sustainability resilience productivity production. Considerations that is climate change, soil quality, etc, all in one single target. Clearly, this would require an approach that captures these different dimensions or aspect of aspects of the sustainability. The indicator that was submitted to the inter agency and expert group on sustainable development goals and was approved in March 2015 is proportion of agriculture area under productive and sustainable agriculture. Now the indicator is tier two, which means that methodology for the indicator has now been approved and indoors. In fact, it was approved by the IAEG SDG in October 2018. However, further required refinements were carried out in the biodiversity sub indicator that we will cover in detail. In 2019, and the final approval was given by the IAEG SDG for the entire framework of SDG 2.41 in November 2019. Now, as I mentioned the indicator is tier two, so the methodology established but very few data points are currently available. The formula that we propose to measure the indicator is simple and straightforward. Its area under productive and sustainable agriculture divided by agriculture land area. So let us focus on the denominator first which is agriculture land area. It is defined as arable land plus permanent crops and permanent models and pastures. It's a well known and established concept that is collected by statistical bodies in countries and compiled internationally via a questionnaire by FAO and is disseminated through FAO staff. The issue obviously is with the numerator of the formula. How do we measure area under productive and sustainable agriculture. Now, what is clear from the description of the target that we covered on the on the previous slide. We have to look at sustainability across all its three dimensions that is economic, social and environmental. Meaning the agriculture area under productive and sustainable agriculture will will be the agriculture area of all those farms or agriculture holdings. So that satisfy the sustainability criteria for all the sub indicators that have been selected across all these three dimensions of sustainability. Here are the steps that were used in the methodological development process of as you two for one. We discussed and chose the scale of assessment for as easy to for one. And the choice made for two for one was to adopt a bottoms up approach, whereby we selected farms or agricultural holdings level sustainability that is aggregated at the national level. We then determine the scope of activities of the holding to be covered by this indicator, and the choice made for as you do for one was to cover only crops and livestock activities. We then reviewed the dimensions to be covered, and we decided to stick to the classical dimension of sustainability that is economic, social and environmental. Let me add here that in the beginning of the process, when we embark on the development of the indicators methodology, we selected five dimension that included in addition to the three already mentioned that is economic social environmental to other dimensions. Those were institutional or governance and resilience. However, later, during the process. It was decided to integrate resilience with the economic social environmental dimensions and drop the governance dimension as part of the methodology of as you do for one. We are exclusively focused on agriculture holdings or farm level assessments. We then zoomed into what we call teams or aspects within each dimension. And then we selected the seven indicators that are needed to measure progress within within each team or aspect. In total, as for the framework of SDG 241 is concerned, we have 11 teams and 11 sub indicator to measure progress within those teams. So we have three indicators in the economic dimension, three in the social dimension and five in the environmental dimension. To establish the sustainability criteria, also known as thresholds or cut off points for each sub indicator to classify the farms and agriculture area that it owns manages or operates by assigning it red, yellow and green statuses, which we call the traffic light approach, we will go through it obviously in detail as part of the sub indicator separately. Obviously, one other decision that we made was selection of the data collection instrument for collecting and reporting data on indicator, which was preferably, you know, agriculture surveys or farm service. We also discuss to decide on the periodicity or frequency for data collection and reporting as you do for one. And it has been set at three years. So countries are supposed to collect and report data on the indicator every three years. And finally, the modality for reporting the indicator. For this we develop both a dashboard where all the 11 sub indicators and teams are presented in one chart where each sub indicator is illustrated separately by sustainability status that is the traffic light approach, which I, which I just mentioned, and an aggregate SG 241 that can be calculated or derived directly from the dashboard. The principles that were used to develop this indicator. First, and the foremost policy relevance action ability. We wanted to make sure that every sub indicator selected as part of SG 241 framework had a meaning for the policy makers, and thus provided information based on which informed decisions can be taken to improve the situation on the ground. Finally, the sub indicators must be easily understood. This was the reason why they have been selected in first place. And once the information is collected, and the results are, you know, derived, it should be easily interpreted by the policy makers. For example, so you know the policy makers should know is agriculture sustainability declining and why and which policies needs needed to be implemented to address these issues. The versatility and comparability are fundamental. We are in SDG process, universal process. Thus, we wanted to make sure that the indicator is applicable or valid everywhere. That is, it must be relevant to all countries of the world, both developing and and developed. The versatility and cost effectiveness were very of very high importance in our mind as we were trying to find a right balance between an ideal indicator from subject matter perspective or technical perspective. And that can be measured consistently with the reasonable cost. So the affordability of the indicator in terms of data collection and reporting was obviously our, our top priority. So to corroborate on this very point further, there are many sustainability issues or aspects, but their measurement is difficult complex or would involve costs. In terms of data collection, etc. that cannot be sustained in the framework of a regular monitoring exercise. So cost effectiveness is also related to measurability. The cost associated with indicator measurement have systematically been considered in relationship with the accuracy and reliability of the results obtained through different measurement options. And finally, minimum cross correlation between the between the indicators. So this was totally discussed. That is, in selecting a limited set of teams and sub indicators. In the framework of the city two for one efforts were made in consultation with the experts to reduce cross correlation between different sub indicators. Obviously, high cross correlation would imply that two or more sub indicators are capturing the same sustainability team or at least issuing capturing the same sustainability phenomena. In this case, the inclusion of one single sub indicator instead of several would be sufficient to adequately measure agriculture sustainability performances. Obviously, all these decisions in terms of policy relevant section ability universality comparability, measurability and cost effectiveness and cross correlation had an implication for the choice of the sub indicators for the different dimension. The choice of sustainability criteria for each indicator and the type and level of sophistication in data collection. Next to the measurement scope. As I explained earlier, we are interested in assigning agriculture area sustainability statuses. So the basic unit of observation and measurement that we have chosen our agriculture holdings or agriculture farms with focus only on those that primarily produces crops and livestock, or a mix of crops and livestock. And obviously, the, the, the basic objective behind you know us selecting crops and livestock producers is to see as to whether these are economically feasible environment friendly and socially acceptable agriculture holdings. So, we focus on crops and livestock production systems. We also include both intensive extensive and subsistence agriculture holdings, as long as their primary activities as, as earlier explained our crops livestock livestock or mix of both. These agriculture holdings may include both food and non food products and crops grown for further or energy purposes. Secondary activities this is this is very important. Secondary activities are considered like say for example aquaculture agroforestry. And if and only if these activities takes place on the agriculture land area of the holding apart from crops and livestock. So the first condition and the necessary condition for us to select an agriculture holding in within the context or for us to do for one is to is to focus on crops and livestock producers. In any case if they are performing additional secondary activities in terms apart from crops and livestock and then those will be considered otherwise not. What is out of scope holdings that are exclusively focused on on other activities, apart from crops and livestock. This holding exclusively focused on aquaculture or agroforestry as primary activities are excluded production from gardens backyards and hobby farms is also out of the scope of a C241. So is the food harvested from the wild. And as well common land that are not exclusively used by the agriculture holding for production of crops and livestock and a mix of both. An important point that I would like to emphasize is that nomadic pastoralism is also excluded from the scope of a C241. As you may know nomadic pastoralism is a practice of rearing livestock by moving with animals from places to places in search of pastures. In fact, it's a way of life of people who do not have who do not live in fact continually in the same place but move cyclically or periodically, or seasonally from one place to another. The frequency or reporting frequency of the indicator is set at three years, as I explained earlier on in the on the previous slide. And this selection of three years is due to various considerations. First, the C241 measures progress towards more productive and sustainable agriculture, and for many sub indicators selected, it is unlikely that their values will change from one ear to another. So these sub indicators, which we will see captures or measures structural phenomena, which doesn't change from one ear to another. Hence, more intense periodicity of reporting is redundant. Secondly, the three year data collection and reporting will enable countries to have at least three data points on the indicator before 2030. Assuming that they start reporting in an in an year or two. So in turn, help countries make a historical trend to assess their performances over time, and also benchmark it or compare it with other countries or peers in the region. And lastly, and obviously, the three years periodicity was set to minimize data collection and reporting burden on the countries. As mentioned earlier, as you do for one current methodology is designed where information is collected through farm service sustainability assessments are made, and final results are expressed as a national value. However, the methodology is scale independent and can be adopted for any administrative or geographic geographical level. And though we understand that any introduction of additional stratification variables will certainly have implications for the sample size, and thus the cost of data collection. So in order to further enrich the analysis for informed and national policymaking. The indicator can be disaggregated at a sub national level. And according to the different types of agriculture holdings that is household non household crops, livestock or a mix of both crops and livestock, and the fact as to whether this agriculture holding is using water for irrigation or not. Apart from that, we can further stratify the sustainability assessments, as I already mentioned, at a sub national level by size of agriculture holding or farm and the gender of the holder, etc. Now, as mentioned earlier, the indicator is multi dimensional. This light represents a matrix or a table that includes everything that we need to know about a city to for one towards the extreme left. You can see that the indicator car cut across the three dimensions of sustainability that is economic environmental and social. And within each dimension. We have a team. For instance, you can see that within the economic dimension, we have three themes and corresponding three sub indicators that are used to measures to measure the progress within that particular team. So within the economic dimension, we have land productivity profitability and resilience and respective sub indicator that measure progress within within each respective team. So for land productivity, we have firm value per hectare for profitability team we have net farm income for resilience team we have risk mitigation mechanism, and so on. Next we have five teams in the environmental dimension and three teams within the social dimension. So as I was mentioning earlier, and total we have 11 teams as you can see here, and 11 sub indicators. Now, the original discussions that we, we carried out with the with the sustainability experts. The list of themes and sub indicator to measure and monitor sustainability is much longer. However, there was this feeling that capturing 11 in total would be a very good step forward. One other important consideration to take note of is that we have developed, we had to develop in fact a universal framework for it to be globally applicable. So a framework that covers the entire spectrum of agriculture, that is confronting sustainability issues that varies from one country to another, or one region to another within the same country, or one type of agriculture production system to another. So, we have to develop something, you know that is that is equally useful and and applicable to all kind of farming systems across the globe. One additional point that I would like to highlight here and then we will later explain it during my next presentation is the recall or the reference period for the for the sub indicator. As you can see here. And as I mentioned earlier, sustainability is a structural concept. This would require a much longer period to assess the problem or issue and make judgment about the farm performances. So as you can see here for some of the sub indicators which are more structural in nature. We have set the recall or the reference period for data collection to to three years instead of one year. So as I said on the previous slide. The first choice for us was to limit the framework of SG 241 to 11 teams and 11 sub indicators. A series of expert discussions in meetings consultations and literature review that we carried out have shown that sustainability is is so complex that in general. The longer list of issues are considered and used to capture a capture the sustainability in agriculture. And this slide as you can see some issues that are considered important, but are not captured within SG 241 framework. We still as I recommended countries to consider these themes, if these are relevant in their national or sub national context. In order to assess the sustainability of their agriculture at a national or sub national level, but from from reporting perspective we we don't need countries to report on these additional themes or sub indicators. One critical aspect that we will discuss in detail as part of the sub indicator in the next presentation was the development or establishment of thresholds or sustainability criteria that are used to assign sustainability statuses to agriculture holdings and the agricultural land area that it manages or operates. Briefly, the thresholds are a cut off the threshold or sustainability criteria are national policy based or international targets or science based absolute or relative values or levels below or above which for each sub indicator. The agriculture holding is assigned sustainability status. So for each sub indicator, a criteria to assess sustainability statuses or levels are developed. Now in order to capture the concept of continuous progress towards sustainability, a traffic light approach was devised in which three sustainability statuses or levels are considered for for each sub indicator. This is called a desirable yellow acceptable and and red unsustainable. This traffic light approach acknowledges the trade off existing between sustainability dimensions and the teams and the need to find an acceptable balance between them. So, so each sub indicator is assessed at the level of the agriculture holding, which is the unit of observation and measurement for us. And there after the sustainability level is associated with the agriculture land area of the culture holdings. And then, you know, all the results are aggregated at the national level by by by this traffic light approach. So getting from the previous slide, the reporting of a CG to for one can be done at various levels using both the dashboard and aggregate indicator. What we require countries to report on is a dashboard and aggregate indicator at the national level. Okay. What makes the dashboard more appealing is that it helps visualize the performances across the dimension. So there we lost you for a little bit. Is it okay now. Yes. Okay, so let me let me, did you, did you lose me on this slide or on the previous one. No, no on this slide on this slide. Okay, okay. So I was saying that, you know, recollecting from the previous slide. I said that the reporting of the indicator can be done at various levels using both a dashboard and aggregate indicator. At FAO, what we require countries to report on is the dashboard and aggregate indicator at the national level. What makes the dashboard approach more attractive is that it helps visualization of the performances across the dimensions, as well as across independent teams and sub indicator separately. In addition, this makes the dashboard policy relevant and actionable for decision makers. As it gives them the tool to quickly check at a single glance where the major sustainability problems lies where to put in emphasis what policies needs to be put in place and resources diverted or directed to address it to improve the situation and to move towards more infrastructure. Now, one additional added advantage of the dashboard is that it allows the possibility of combining information from different data sources that we will discuss in the in the in the next presentation. Now, to exemplify the dashboard for SG241. It's a, you know, the chart that you see here on on on this slide. As you can see here on the horizontal axis or the x axis, we are measuring teams, the 11 teams or the sub indicators on the vertical axis. We are measuring the percentage of agriculture area or proportion of agriculture area. Now the computations and construction of each some indicator is carried out separately. Sustainability assessments are made for each some indicator at the agriculture holding level. After all agriculture holding level results are associated with the agriculture land area of that particular holding. And thereafter, you know all these results are aggregated at the national or sub national level by sustainability statuses that is red yellow green and finally reported in a chart like this which we call dashboard. As I mentioned earlier, the indicator is scale independent. So if the country wishes to report result at the sub national level for making informed policies, then the stratification variables or level of geographic disaggregations must be planned in sampling design of the farm survey beforehand for it to be able to do so. The final aggregate indicator as you do for one is derived from the dashboard at the country level. Now let me just go back to the previous slide. So here you can see each sub indicator separately by its sustainability status. While the final number of sg241 is the result of the sub indicator that has recorded the highest unsustainability performance. This can be easily done either using the formula on this slide. Thereby we identify the sub indicator that has recorded or reported the minimum of sustainability performance. Okay, the minimum of acceptable or desirable across all the 11 sub indicators are the maximum of the unsustainable performance across the 11 sub indicators. The performances of countries over time can be measured by the change in proportion of agriculture area that is unsustainable. So we can either track this and see what time as to whether the country has improved or deteriorated and in terms of its performance is over time or conversely by tracking the value of this formula which is measuring sustainability. In this case, we are focused on tracking the level of sustainability and we will see if the country has improved the value of this particular formula would increase. But going back to the dashboard as you can see here, as I mentioned the aggregate indicator is the aggregate 241 value is of the indicator that has reported the highest level of unsustainability or the lowest level of sustainability performances. And as you can see here from the chart you can easily, you can easily visualize that, in fact, indicator number two, which is which is not from income or profitability team has recorded the highest level of unsustainability or the lowest level of sustainability performance. And hence, for this particular country, the aggregate value would be 40% for the aggregate SG241. Now, we said in the beginning that policy relevance is a very important consideration in context of SG241. And in this respect, the dashboard approach that we offer or we propose to countries is really interesting as it provides a structured and transparent framework to measure and report on sustainable agriculture. It allows focus on main issues related to sustainability and encourage decisions by linking it to policy actions. And lastly, it drives the policy towards agriculture sustainability issues with focus on intervention at various levels. Obviously, the dashboard approach as you saw on the previous slide here is easy to interpret in terms of the extent to which the country agriculture is far from being productive and sustainable. And it's very easy to identify and prioritize the areas that require intervention. So as you can see here at a single glance you can see that in this particular country, the main issues related to sustainability are within profitability resilience and soil health themes, as well as some attention needs to be paid to decent employment. So I stop here. Please let me know if you have any question until so far regarding the content that we have covered up until now. Stefania, the floor is yours. Okay, thank you. Yes. Welcome back. So, let's resume the training. We have seen this morning better today because it is this morning the afternoon at this evening, according to where you are. So we have seen the SDG to for one background, the scope, the periodicity levels, limitations, the policy use. Let's move to the framework, which is the core content of this training. And we will see in details the three dimensions with all the 11 sub indicators. As from there we show you today probably only the economic one. But let's see so let's start again the meeting source immediately so as from there you have the floor. So, thank you very much and welcome back everyone. So let me immediately share my screen with all of you. So, in the previous presentation, we learned about the conceptual and methodological basis of SDG to for one that is its scope coverage themes sub indicators periodicity and reporting etc. In the next presentation, we will go through the 11 themes and 11 respective sub indicators of SDG to for one, particularly focusing on the rationale for selection of the team and the sub indicator. The data items required to construct the sub indicator and the sustainability criteria developed to assign the agriculture holding and its agriculture land area. So as highlighted earlier, as did you do for one is defined using a simple formula, which is area under productive and sustainable agriculture divided by agriculture land area. So let us focus on the denominator. Agriculture land area. So the concept is the one FAO land use classes, and as such countries provide national level statistics annually via the relevant FAO study questionnaire. So the concept is the same. Very importantly, the same land use classes are collected by census, which automatically addresses the issue of the common land. So remember, we in the context of 241 weeks to common lands from from the scope. So in other words that the agriculture censuses does focus only on farms, just like 241 and exclude common land along the lines of message to for one. So we concentrate on agriculture land area well established concept, which is derived by adding cropland and land under permanent matters and pastures. One important point to keep in mind is that for estimation of agriculture land area. We adhere to the system of environmental economic accounting agriculture forest and fisheries, and what senses of agriculture 2020 standards and classification systems. So as you can see here, we are only interested in agriculture land area. So these are the classes which are, which are taken into account for us to estimate the agriculture land area of particular holding, which is, which is again, let me emphasize the denominator of the, of the formula. Another important point to take note of is the land tenure of the agriculture holding and agriculture land area that it's managing, particularly from SCG to for one point of view, the scope include the entire agriculture land area, which is owned and operated. Okay. Which is rented in or land which is borrowed for free or occupied. Now, common lands, as I explained earlier, are out of the scope of SDG to for one, unless these common lands are exclusively managed by the agriculture holding for its operations on the, what is out of scope. The land tenure perspective is land rented out so land owned by the agriculture holding. But if it is rented out to other farms, then it will be out of the scope of the indicator. So, just as an example, it's a, you know, of an agriculture holding, it has four parcels of land parcel one parcel to parcel three and parcel for. And if we go by the explanation which which I just illustrated parcel one consists of two fields field one and field two, and it is owned and used by the agriculture holding itself. So it will be part of the scope of this is to for one parcel to solve also composed of two fields. It's owned and use so it will be part of the scope. So it's not owned by the agriculture holding, but it's rented in from another from another farm for agriculture activities for this by this particular holding and hence it will be considered as part of the scope of the agricultural and area of this parcel three, though it's owned by the agriculture holding, but it is rented out for that particular air or for for an extended period to another agriculture holding so it won't be considered as part of the scope of agricultural land area of this particular area. So it is excluded. Now, this slides slide again illustrate the framework office you two for one the three dimensions economic, environmental, and social 11 teams 11 sub indicators, the type of agriculture holding to which this particular sub indicator is applicable and the reference period, which we, which we will discuss as part of the each sub indicator separately. So as you can see here. So one of the question raised by one of the colleague in the previous session that food security. Sub indicator is not applicable to non household agriculture holding so. Sub indicator is only relevant to household farms. And in terms of decent employment wage rate in agriculture, this sub indicator is only applicable to holdings that are hiring unskilled or routine labors, we will explain this as part of the methodology of of this particular indicator. So, before going into the details of respective sub indicator, let me provide you with with some generic steps. Okay. That are that that are common for all sub indicators and will be used to estimate each sub indicator. Once relevant qualitative information is collected through agriculture surveys, and thereafter checked cleaned validated and stored on a computer as an Excel spreadsheet or some other statistical package. It must then be transformed into appropriate quantitative variables. Data primary variables data in turn used to construct the 11 sub indicators. So we collect qualitative information through agriculture surveys or other other surveys as a matter of fact, through set of questions. Okay. These set of questions are then used to estimate primary variables. Primary variables are then used to construct secondary variables and those secondary variables are then used for construction of respective sub indicator. Now, these steps are elaborated in the in the PDF file which is, which is attached to this slide. But however, you know, it will get clarified as we as we move along. The first sub indicator in the economic dimension is farm output value per hectare or land productivity. The dimension is obviously economic, the team is land productivity. The coverage for this particular sub indicator is all types of agriculture holdings. And the reference period for this particular. Sub indicator is last calendar year. Now, let me explain as to what we mean by farm output value per hectare land productivity is a measure of agricultural value of outputs obtained on a given area of land for a given period of time. For a farm level or agricultural holding level land productivity reflects the technology and production processes for a given agroecological condition adopted by that particular culture holding. Now, in a broader sense, any increase in the level of land productivity enables higher production per unit of land, which is which is straightforward right. Now land productivity is driven by combination of multiple factors which include climate soils topography land use and land management. In addition, land productivity varies not only in space in terms of all these factors which I just explained, but also in time. This variability in land productivity occurs at different timescales from seasonal to inter annual in response to many factors of which one is variability in rainfall or other weather related patterns. In the context of 241, we use the same classical approach to estimate land productivity that is first the farm output value in local currency units is estimated, which is then divided by agriculture land area measured in hectares. And lastly, the farm or agriculture holding productivity is then compared with the farm output value per hectare or the land productivity of the distribution of agriculture holding to which this farm belongs to assign the agriculture holding red green and yellow statistics. Now, for this particular sub indicator. We are interested in the following data items. So let's first concentrate on the formula. So the formula is fairly straightforward, it is, you know, a typical formula for estimation of land productivity farm output value per hectare is equal to farm output value in local currency units, in the agriculture land area of the agriculture holding in hectares. So from this perspective enough for us to estimate the farm output value, what we need is obviously the value of output, which is nothing but physical quantities multiplied by the farm gate prices. The main crops and it's by product produced by the holding in a reference period. If this holding is primarily crop producer five man livestock, and it's product produced by the holding in a reference period, if it is primarily livestock producing holding, or a mix of both crops and crop if it is a mix producer. As I mentioned earlier, other activities performed by the agriculture holding will be considered as secondary activities, if there are any. So other on from products produced by the holding in a reference period on top of crops and livestock. Okay. So what we need is agriculture land area of the of the holding and we define the agriculture land area right. It's crop areas or arable land plus permanent crops and permanent metals and pastures. We further need categorization of the agriculture holdings and this will get explained in the in the next slide as to as to what do we mean by that. And obviously, we then need to estimate because we are comparing the farm that the given farm productivity against the, the productivity of a distribution of agriculture holdings to which this holding belongs, and hence, we would need, you know, the farm output value per hectare for the distribution of farm selected as part of the, of the sample. So all of the information that is required for us to construct this sub indicator is in fact, you know collected to a set of questions which are part of the survey module of sg241 that we have developed and we will show you later on. So, in terms of crops, and it's by product list, I just given you an example. Obviously, the list of crops would vary from one country to another, and within within a country from one region to another. And, and, but this is just to just just to give you an example. So by no means this is an exhaustive list or a list that FAO is recommending, but this is a this is just an example. Okay. And in terms of us estimating the value of output for for a crops, we are not interested only in the physical quantities of crops, which are, you know, which is one part of the equation, but we are also interested in the byproducts so once the crop is harvested, there are certain byproducts produce apart from the main crop, which may be of value to the farmer, and he may be selling it or using it for own consumption. So from this perspective it's, it's, it's worthwhile to estimate those and add those to the value of output. For other activities, there could be a range of other farm activities, you know, which are secondary to crops and livestock. So there could be some kind of processing going on there could be, you know, production of agroforestry products, there could be production of, you know, other activities. For example, making hand handicrafts training of animals, etc, etc. So if there are any other on farm activities undertaken by the agriculture holding apart from crops and livestock as a country activities those those the way their value of output needs to be estimated for us to arrive at the total value of output of the culture holding for that particular for that particular period. As I was mentioning earlier. And we covered this as part of the earlier presentation. Typically for for the farm output value per hectare of for land productivity sub indicator, it's, it's recommended that the agriculture holdings are characterized or grouped by by different types. What do we mean by that. I explained that as part of the previous presentation that we could have three certification with variables right one is household non household. The second one is crops, focus farms livestock focus farms, or one that produce both crops and livestock. The third one is as to whether this holding is using water for irrigation or not. So, based on, based on all these three, you know, variables, we can, we can group the farms by different types, or we can categorize the farms by different types. So, and a different combination and permutation of these variables will give us different types of agriculture holdings. So let's say for example, I give an agriculture holding could either be household sector agriculture holding producing on the crops, and it's using water for irrigation. So, this particular category of farm is called crop household irrigate. There could very well be, you know, an agriculture holding, which is non household focused on crops and using water for irrigation. Okay, so this this is another category of agriculture holding based on based on this definition. Now, remember one thing. Why we are, you know, using this detailed drill down stratification variables for us to estimate the productivity. The underlying reason behind us having these different categories of farms is that the productivity of these different agriculture holdings will vary from from the type of sector that this particular culture holding belongs to. As to whether it's producing crops, livestock products mix, or as to whether it's using water for irrigation. So, hands to capture. To first estimate precise productivity of the agriculture holding and then compare it with, you know, and a distribution of agriculture holdings, which are producing similar kind of products and separating and similar kind of circumstances. For us to, for us to have a reasonable sustainability assessments. So the basic idea behind this is for us to compare apples with apples and not to compare apples with oranges. So that's the underlying idea behind us having recommending you know this different categorization of agriculture holding. Using this permutation and combination of different, you know, stratification variables, we will arrive at 12 different categories of agriculture holding. Now, for many countries not not all these 12 different categories will be applicable and that's just fine. So some countries may have maybe only four or five categories applicable to them, but that is okay. So, what then we do is, you know, the, once we categorize the agriculture holdings by different types, using the three certification variables, we then have all the necessary ingredients for us to estimate farm output value per hectare. And I mentioned to you that farm value, farm output value per hectare or land productivity is simple to calculate its farm output value of the products that it is producing in the reference period divided by the agriculture land area. Now, this is, this is an example of of a typical agriculture holding. You know, and how do we approach estimating the farm output value. So as you can see here in the formula, it's physical quantities into into prices. So, basically, let's focus on holding holding one. So the holding one produce different varieties of rice, maize, and then you know a couple of byproducts are produced as on top of the primary production of crops. Now, obviously what we need is physical quantities in in some measurable units. Okay. And then the farm get prices per unit of that particular product. So why we are using different varieties of rice because their prices varies in the market, and hence, they're the value of output of each particular variety would be different. You know, one would be different from other, and hence to estimate the accurate farm output value. It's better for us to have these distinguished. We estimate the output value by crop. So we estimate the physical quantities by the farm get prices we estimate the farm output value and we do repeat this for for all the crops that they culture holding is producing. And then we added up to arrive at the total farm output value. So once this total farm output value is is estimated, all we have to do is to divide it by the the agriculture land area which will be measured in hectares. Now, once the farm output value per hectare for all the farms for all the agriculture holdings. Okay, that are part of the sample of that particular agriculture survey. Has been calculated. Of course, I mean as I mentioned, all these farms are categorized by different groups. Okay. So for each category of farms, we then order the farm output value per hectare from lowest to highest. You can have four or five or six different distributions. You know, for the agriculture holdings that are selected as part of the sample of the culture survey. So we order the farm output value per hectare or the land productivity. For each group of farms from lowest to highest. Once we do that, we identify the 90th percentile. This is very important because the 90th percentile is then going to be used for us to have the sustainability to derive the sustainability criteria threshold remember for each sub indicator we are assigning red yellow and green statuses so we have to do that based on based on certain values, okay above or below or between which the farms will be assigned green yellow or red statuses. So from this perspective, let me reiterate, we order the productivity by each category we identify the 90th percentile, the calculation of the 90th percentile is very easy. So it's the total number of the observation multiplied by the 90 90%. In this case, for this example that I'm showing you the 90th percentile for for the for these categories of farm is estimated to be the productivity is estimated to be 600. Okay. So once the 90th percentile is identified and the associated productivity is is marked with 600. We then multiply the 600 with two third and one third. These are the two thresholds that then we are going to use to, you know, basically assign the agriculture holding sustainability status. So two third of 600 is 400 one third of 600 is 200. And these are the two thresholds against which the productivity of a given farm will benchmark. Okay. So these two thresholds which I just explained. Okay. We then use to assign red, green and yellow sustainability statuses to the farms. And, you know, once we, once we classify the farms, green, yellow and red, we then assign the same status to the agriculture area that it owns manages or operates. So, as you can see here, the agriculture holdings will be given green or desirable status if a given farm land productivity or farm output value per hectare is equal to or greater than the value corresponding to the two third of the 90th percentile is obviously estimated for the distribution of categories of farms to which this farm belong. Now what do we what do we mean by this. So if a farm productivity is above two third of the 90th percentile to the of the distribution, then you know this farm will be assigned green status. If the farm output value per hectare is between one third and two third of the 90th percentile. So if a particular distribution to which it belongs, it will be assigned yellow status, and if the farm output value is less than the corresponding value of one third of the 90th percentile then the farm will be assigned red status. Now, again, just to give you an example. For example, mind you is some some information or the data that we are showing you here is from the pilot tests that we conducted in Bangladesh back in 2017 and 18. So as you can see here. We collected information. 400 farms or agriculture holding Bangladesh. And we then estimated the productivity of each particular agriculture holding within order the productivity of agriculture holding from lowest to highest. We identified the 90th percentile. Each category of agriculture holdings, and then we estimated the two third and the one third percentiles of the two third and one third of the 90th percentile. And as you can see here it varies from one category to another. Otherwise, we wouldn't, we wouldn't have recommended, you know, us to have countries estimate pro activities by different categories of funds. So livestock households sector irrigated the 90th percentile for this particular categories 800 two third is 533 one third is seven and so on. So we do it for the all relevant categories to which this agriculture holding belongs. Now, as I mentioned, so the individual farm productivity is then benchmarked against the one third and two third percentiles of the distribution. So as you can see here, the for agriculture holding one is estimated to be 900. It belongs to crop household irrigated sector. For this particular category, the 90th percentile based on the, the productivity of the entire distribution is estimated to be 600 two third threshold is 400 the one third threshold is 200 and so on. So now this is the critical area. So we then compare the individual farm productivity with these two thresholds. As we can see here the land productivity for this particular holding is greater than the two third of the 90th percentile, and hence this holding will be assigned as a green and by virtue of that the culture land area that is holding operates is assigned green status. Okay, so this holding has is operating only 0.9 hectares, but by by the logic that I just explained, it is assigned, you know, green status. Now for holding to, as you can see here, the threshold which I explained on the previous slide, let me go back. Sorry, my screen is stuck. So as I mentioned, so the farm will be classified as yellow, if its productivity is greater than the value corresponding to one third, but less than two third of the 90th percentile. So as you can see here, 300 is between 533 and 267 and hence it is assigned yellow status. And for holding three, as you can see here, the productivity is below one third of the 90th percentile and hence it is awarded or assigned red status. Now, let me let me explain all these steps to you using, you know, some, some made up numbers. Okay. Or, or an Excel practice set that we have developed for for for this training. So let me stop my screen here. And let me share with you the Excel sheet. Okay. So, how do we go about estimating the farm? So now we see the email. You see the email. Okay. How about now? Perfect. Yeah, coming. Okay. Is it okay now? Yes, yes. So, you know, I, in my, in my previous presentation, I was telling you about the survey module that we have developed for SCG 241. Of course, that survey module was shared with you as part of our earlier communication. But we will show it to you later during the, the sessions, maybe tomorrow or day after. So what is this survey module about the survey module consists of all the questions that are needed to collect information on and let her construct the respective elements of indicators. So in this particular exercise, we will show you as to what are the questions relevant to particular sub indicator. And once information is collected, then how do you use that information for you to construct the sub indicators. So for the land productivity sub indicator or a farm output value per hectare, we have, you know, the following questions in the, in the survey module. So the first question is what was the total value of crops and it's by product produced by the holding that reference period is last calendar year. And, you know, at least we, we, we ask countries to at least list five main crops, and it's by product produced by the Holy. Now, these crops could either be less or more. It doesn't matter for a given holding maybe focus only on one crop or it may be focused on on seven. That that is just fine so irrespective of how many crops the holding is producing we have to list all of them. In this particular case, as you can see here. So in this question we asked about the crop name, the area that the holding used to cultivate that crop the unit of measure. In terms of area, the quantity produced the physical quantity. Quantity unit of measure. The average or the latest price per unit. Of course, all these average and latest price per unit as I explained earlier, our farm get prices so we're not talking about wholesale or retail prices, we're talking about farm get prices. And then you know the last column which is which is basically, you know, the calculation based on the information which is which is shown here. Now, for some of the agriculture holdings they may not have, you know, records of how much quantity that produce and what was the average or latest price per unit that they were able to get for for those particular products so in this case instead of asking the information about quantity produced and average price. The farmer may be more comfortable providing us with the information on directly on total value production for that particular problem. So, which is just fine so in this case we won't need this information we would only collect information on on value production, but either way it's fine the more precise ways for us to collect information quantities and the prices and then be estimated ourselves, or we ask the farmer, if he doesn't have an idea about the prices and the quantities then we ask directly him about the total value production. So this is about the crops. Okay. So once this information is collected, of course I mentioned in mind in my presentation that we not only collect information on the core crops. produced, but we also collect information on the on the byproducts of crops. So as you can see here, there could very well be byproducts these could be named differently in your country context but that is just fine. So, like say for example with mace, you know straw or stock is produced with rice straw husk is produced for cotton sticks are produced for wheat stocks are produced. You know it could be, it could be named differently in different countries, but the idea is to capture this as well as part of the calculation of farm output value. So what we, again, it's very straightforward. What we need information on is the quantity produced the unit in which that particular byproduct is is measured. The average or the latest prices, again, these latest or average prices are for the farm gate prices. Okay, so these are not retail retailer wholesaler or distributed prices. And then obviously, the total value of production of this particular of this particular crop with this particular byproduct. I mean the value is not showing up, but this is total value of production. Okay. So we collect information on the, on the value of crops, we collect information on the value of byproducts of crops. So let's assume. For, for instance, that this agriculture holding is also producing livestock and its products, which is the scope of this indicator 2.4.1. But there could very well be the holding for which livestock is non existent but that is just fine we just collect information on this and we skip all the questions related to livestock. But if there is some livestock operations, then we have to consider that for us to estimate the total output value of livestock. Now, again, the question is, what was the total value of livestock and its byproduct produced by the holding the reference period is last calendar year. And again, just for the sake of simplicity, we ask about the five main livestock and livestock products, these could be more or less, it depends right. But in any case, five is a good number to start with. So it, what I'm trying to emphasize is that collecting information on five is, is not mandatory. Okay. Now, there could be a variety of different livestock animals raised or, you know, raised by the agriculture holding horses cattle sheeps goats camels pigs, depending on the content context it will change. This is just a, just a list that we have provided it could be anything. What, obviously, the, all those who are parts, part of estimation of national accounts know that it's always better for us to estimate the balance of the livestock in the beginning of the year. And then what was the balance towards the end end of the year and how much was carried forward from carried over from last year, and what will be carried forward to the to the next year. So, number of heads of livestock at the beginning of the year. So for horses it's 10 number of heads bought or received during their five numbers of heads, given away dead or slaughtered during their three number of heads sold paid to labor, rented out or exchange during their 10 number of heads, you know, at the, at the end of the year is to so what we do is we take this, we add this, we subtract this and we subtract this and we arrive at the final value of livestock at the end of the year for for a given agricultural holding. And then obviously, as a second variable, or that we need for us to collect data on is the average or latest price per unit. Okay, of that particular, of that particular livestock. Now, these average or latest prices, again, as I mentioned, these are farm gate and would vary from one country to another and within within a country from one region to another. So it's, it's, it's always good to ask about the prices and not to use one average price for the entire country because that would be that would either, you know, underestimate or always overestimate the value of output for that particular livestock. or spatial. So then we estimate the total value of production for that particular livestock head and for that particular air and we do the same for all the livestock that are produced or raised by the culture holding. Okay. And again, the logic is again the same. So we either ask about all this information. Okay, which is more detailed and precise. The quantities and as well as the prices or we directly ask the farmer, if he doesn't recall, if he's unable to recall all this information, then we directly ask him. Okay, fine. Tell me what was the total value of output that you generated, you know, for horses or for cattle or for sheep that you are growing or raising on your agriculture hold. Now, so once we do that, obviously we know that there are certain by products or products that are produced as a result of livestock operations on the farm, it could be horns, it could be milk, it could be fleece it could be bull, I could be any other thing right, which are produced as part of the typical livestock operations. So, again, we are interested in the total quantity produced for that particular product. The unit of measures in kgs, or maybe liters or maybe some other physical unit. The selection of unit is not important for the, we need to be very precise in terms of, you know, documenting the unit. So that should be that should be documented properly. So, let's say for example, you know milk is in some countries it's measured in kgs in other countries and liters will in some countries in kgs, you know, maybe some other countries are using some other physical unit of measure. What, what important is that the average or the latest prices, the farm get prices then needed to be in the same unit. Okay. So, if the milk is estimated in liter, then the price should be per, you know, whatever currency unit, local currency unit per liter, okay, that's important. So, we need to make sure that the quantity and the prices are reflected in the same units and the total value of production. Okay, so the total value of production again the rationale is, if the farmer doesn't have information on these, then he can directly provide us with the total value of production for the entire year for that particular product. So once you know information on the value of output for livestock and the value of output of its products and the value of output of crops which I showed you showed you above. Right, it's by products and products once this is estimated, we have everything that we need to estimate the numerator of the productivity formula, which is from output value and local currency units. Now, on top of these two activities which are crops and livestock. Okay, I mentioned to you that if the holding is producing other on farm activities as secondary activities then that then those needs to be captured. If you don't capture it, then, you know, we will be underestimating the productivity of that particular culture. So let's say, for example, on top of crops and livestock is primary products, if the holding is producing, you know, other other processed, you know, agriculture commodities, like say for example, flour, marmalade, yogurt, cheese, or is practicing eco culture, then you know, all the quantity produced of those needs to be captured as well. Okay, the unit of measures should be should be captured and asked the farmer, you know, clearly, the average or latest price for that particular on from product, apart from crops and livestock should be captured. And the total value of production should be estimated. And then, you know, so these are these are three questions about the numerator of the productivity formula that we would need for us to collect information on. Now what else do we need we need the denominator of the formula which is the agricultural land area of the holding. So as I mentioned to you earlier, from land tenor perspective. For total agricultural land area of the holding, you know, what is in the scope, all land which is owned and operated by the holding, all land which is rented in by the holding, and other land which is occupied including common land that is exclusively managed by the holding. Okay, that's, that's really a key. Okay. So, we add that up, we add all these up to estimate the total agricultural land area of the holding. What is excluded is all agricultural land area that is owned, but is rented out. Okay, that is not part of the scope of the holding, holding agricultural land area. So, this is from the land tenor perspective this is to make sure that we don't include the land on but rented out. So this is this is like you know, a check on the on the estimation of agricultural land. From land use perspective, as I mentioned to you earlier, total agricultural land area of the holding consists of all these categories. Which is arable land plus. So all this is arable land, plus permanent crops and permanent meadows and pastures. Okay, so we need to collect information on all these. And obviously, this will be the same as the one captured above. So from the land use perspective. The total agricultural land area of the holding should be exactly the same as captured in this particular question. If there is a slight discrepancy between these two numbers. So the land total agricultural land area using the question, and the one is introduced in the land use question, then we should re ask this question to the respondent and ask him as to, you know, well he did his responses. Now, so this information all this information is collected what else do we need information on. As I mentioned, from productivity perspective. We, we are interested in, you know, having precise estimates of productivity. Okay, because we are comparing the farm productivity is again with other agriculture holdings. Okay. So, we need to find out as to whether this holding is this farm is household sector farm or non household sector farm. So that this holding is using water for irrigation. Okay. And as to whether, you know, it's a man the crop producer mainly livestock producer, or, or a mix of both crops livestock producer. Okay, as I explained to you earlier, mainly crop producer represents those agriculture holding that produce crops, which represents more than two third of two third of its total value production. So mainly livestock producer, if the tour within the total output value livestock production is is two third or greater, and it will be a mix of both, where when each of them represents equal to or less than two third of the total value of production. So, using all these 1234567 and eight questions, using all these eight questions. We will be able to derive the farm output value for what this particular agriculture hold now how do we do this. So, step one is reports the data on the physical quantities and the prices collected using the survey module. So as you can see here. So, we have the prices per unit. It's mentioned us dollar here but you can use your local currency units. Then we have the physical quantities measured in in units in unit of measurement. So this information is coming from the questions which I just showed you. Okay. So we compile this table. Then the next step is to multiply the prices with the physical quantities. Okay, for us to estimate the value of production for each commodity. So we do that did this for for for all the products. So we do this for individually for all the products. And then what we do is this table is a mere repetition of the same one. The only addition in this table is towards the very end. So by we add up all the output values for the commodities that the agriculture holding. So, it's producing. So this is now the numerator. This is 1477 or 1477 is the total output value. Now the second information that we need is obviously the land use. So let's ask the farmer about his land use. Okay. Obviously, all these categories of land use are well explained in the methodological note as well as the support documents. Okay, in the numerator manual. So we have a series of support documents that we will show you. So all these categories as to what do we mean by temporary temporary crops. You know temporary follow temporary murders and pastures kitchen gardens and backyards. All these are explained there. And once the question is administer the numerator need to explain. To the farmer for him to have a better idea as to what is getting asked of him. So, we estimate the total agricultural land area, which is in fact, three plus six equal to nine. So nine should appear here. In hectares of course. So, now we have the two numbers using which we can estimate the farm output value per hectare for this particular agriculture holding 1477 nine. So we divide this by 1477 by nine using the formula which we elaborated in the slides to estimate 164.11. Now, as I mentioned earlier, you know the categorization of agricultural holding is really very important. Okay, this is for us to compare likes with likes. Okay, so each agricultural holding which is selected as part of the sample of agriculture survey belongs to some category, right, whether either it will be household. It could very well be producing a mix of crops and livestock, and it may be using irrigation or not right and depending on that it belongs to category mixed household sector irrigated and so on. So each agricultural holding will belong to a certain category. So these are the list of 12 categories that I was referring to in my presentation so you can have potentially possibly you can have time you may have less which is which is fine. So this once this is done. So once we estimate the productivity for individual form we repeat the same exercise for all agriculture holdings that are part of the sample. There could very well be 1000 or they could be very well be 10,000 agriculture hold. So we repeat the same step for all agricultural holdings and we estimate their farm output value per hectare and then we categorize them by the different categories using the stratification variables. So once this is done. Once this is done. If you recall, I mentioned to you then for each category. Okay, we estimate the 90th percentile we estimate the 90th percentile for that particular group. Let's say for example, this is for category two, which is livestock household irrigated right. So in this case we order, you know all the agriculture holdings with their productivity is from lowest to highest highest. Then we estimate the 90th percentile which we explained to you so the 90th percentile is very simple. You multiply 90% with a total number of observation in that particular group. Okay, and it will help you estimate the 90th percentile in this case is holding number 18th. We then take the farm output value per hectare or the land productivity value of the 90th percentile and we multiply this 800 with two third and one third to estimate the two thresholds. And now after estimation of the threshold we have all the information that we need for us to assign sustainability status to an agricultural holding. We then see if the agricultural holding productivity is above two third of the 90th percentile for that particular group. It will be assigned green status. If the productivity is between 533 and 267 it will be assigned yellow status. If the productivity is below 267 or one third of the 90th percentile it will be assigned red status and we do the same. For the 90th percentile for that particular group, it will be assigned green status. If the productivity is between 533 and 267 it will be assigned yellow status. If the productivity is below 267 or one third of the 90th percentile it will be assigned red status. And we do this. We identify the 90th percentiles for all categories. We estimate the two third and one third for all categories which are relevant in our case. Okay, so this is simply the explanation that I just gave you the traffic light green desirable yellow acceptable red unsustainable. So, in this case, holding one, the productivity is estimated to be for that particular holding 164. It belongs to mixed household sector irrigated. The 90th percentile value for this particular category is 700 two third of the 700 467 one third is 233. We compare this with these two and see as to whether it falls between it's greater than or less than, and then we assign sustainability status to the agriculture holding. And by virtue of that to the agricultural land area that is managing owning or operating. So in this case as you can see here 164 is less than one third of the 90th percentile and hence it is assigned red status. Holding to belongs to livestock household sector irrigated. Its productivity is between two third and one third and hence its sun yellow status. And holding five. Its productivity is greater than two third of the 90th percentile and hence it is assigned green status. Okay, but we are not done there yet. So we have assigned agriculture holding sustainability statuses. Now we have to basically give this sustainability status to the agricultural land area of that particular agriculture holding. It's a it's a simple straightforward step, whatever sustainability is assigned to agriculture holding that is assigned to the agricultural land area of that particular world. So in this case, the holding area is nine hundred here. It was unsustainable based on based on the logic here, as you can see here. Yeah, it's unsustainable. So the same sustainability status is assigned to its agricultural land area. And so on for all agriculture holding. So we then now as a last step, what we do is we aggregate all the areas which are classified as greens, yellows and reds. Okay. So we add this up. As you can see here. The sum is 44 so we add up all the areas that are classified as green, we add up all the areas that are classified as red, we add up all the areas that are classified as yellow. So we add those up, and then we divide by the nationally representative. Agriculture land area. Collecting using the same agriculture survey for us to estimate the proportion. So once we do that. We now have the areas. Classified agricultural land area classified as sustainable acceptable and unsustainable by sustainability statuses for the for the entire country. And I stop here. So if you have any questions please feel free to ask. Thank you. Thank you. We have already some questions so the first one is why do you adopt the 90% tireless criteria of threshold. Oh yes, this is a very interest important question and trust in one as well because we usually get this question quite often. What's, what's the rationale behind or what's the justification behind 90th percentile why not 50th percentile right or two quartiles. Why not the nine six decide right. So, now, the selection of this particular threshold is is arbitrary as arbitrary as any other threshold could very well be. We, we thought of her as to what threshold can we use for us to assign sustainability statuses and this was thoroughly debated with different experts. Okay. Now, the, the only consensus that we reached in terms of the threshold that we have selected was was nine was the 90th percentile so this is an arbitrary threshold. And, you know, your guess is as good as mine in terms of why 90th why not why not why not 80th, 80th, or why not, you know, 60th. So this is a threshold but as long as we are consistently, you know, using it across all countries for us to compare for activities of the agriculture holdings with the distribution. I believe we are we are good. But this is this is let me admit this is an arbitrary threshold. You know, finalize in discussion with the experts and later on, this was agreed to and endorsed by all all the countries on the members. Okay, thank you. We have a question from Indonesia. So in our pilot of agri-survey last year we only collected data on individuals so household holdings. What do you think about the two for one as the indicator computed from the results of the pilot. Is it okay to be disseminated given we did not cover the known household holding in the pilot? I would say no, because two for one covers the entire spectrum of agriculture holding covering both household and non household sector. So it depends if the non household sector in case of Indonesia is not significant in terms of agriculture land area. But if it merely represent maybe like say for example 2% of agricultural land area of Indonesia, then more or less, you know you collecting information only on the household sector is is okay. But if non household sector or commercial sector or large scale agriculture is a significant portion of your agricultural land area, then of course, you are showing a partial picture and any result based on those partial will be misleading in terms of you representing your agricultural land area is sustainable unsustainable or otherwise. So I would say, you know, if large scale commercial agriculture or non household sector is a significant portion of your agriculture land area, then that should be, you know, surveyed and you know information should be collected from from that sector as well for you to have an entire picture of the of the, you know, agricultural land area of the country. Thank you. Thank you. Thank you. Just for a reminder for everybody, we will have a special presentation from Indonesia on the on the fourth day about the pilots so we can ask them all questions we want on the fourth day. We don't have any other questions from there. Just a few seconds. Yeah, no, no question come up. Another reminder please write your questions in the Q&A section, it will be much easier for me to follow your question. So yeah, we can go, we can move on with the next subindicator. So before I proceed, Sifanya, we are, we have 20 minutes more or less right. Yes. So I will try to finish up the the second sub indicator in the economic dimension, which is net farm income and then then we close for today and then we resume tomorrow. Yes. Okay, okay, so let me share my screen. So the second sub indicator in the economic dimension is is net farm income. So it's called profitability, the coverage is all from types. And as you can see here the reference period for this particular sub indicator is set at three years. I will explain as to why. In the in the coming slides. Now, an important part of sustainability and agriculture is the economic liability or feasibility of agriculture holdings. This, of course, driven to a large extent by its profitability. Within the context of SG241, profitability is measured using the net income that the farmer is able to earn from farming operations. Now availability and use of information on farm economic performances used majored using profitability will support better decisions, both at micro and micro economic levels. Obviously, performance measures drive behavior, better information on performance can alter behavior and decision making by the government and producers, both in large scale commercial farming and medium and small scale subsistence agriculture. So this slide illustrates two options or two approaches that we have considered and recommend to countries, in fact, for them to implement. So the first one is a more sophisticated approach is more sophisticated, more data demanding, but yet more precise as well at the same time. So the sophisticated approach is more data demanding, but is more precise in terms of its estimation of net farm income. And then we offer simplified options as well. So the sophisticated options is given here. So we calculate the net farm income using the following formula. So NFI is net farm income, CR is total farm cash receipts, including direct program payments, YK is income in kind, OE is total operating expenses after rebates, this includes labor cost as well, PEP is depreciation and Delta inventory is value of inventory change. Now, in terms of us recommending the more sophisticated approach, this is basically this approach for us estimating the net farm income of a given agriculture holding is adopted from Statistics Canada, Statscan. As an approach, it is recommended, as I mentioned earlier, it gives you more precise estimates. However, it's used at the country level is conditional if data on farm financial records that are documented on daily, weekly, monthly basis are available. So the more sophisticated approach requires some foundations. So if information on all these detailed variables is collected, then the country should use this approach, otherwise they should go for the more simplified option, which I will explain on the next slide. The assumption is that large scale commercial farms or large scale agriculture holdings maintain detailed financial records using which the net farming can be calculated using this approach. Now, in terms of explanation of all these variables as to what it means and what does it include, all this information is given in the Statscan methodology and as well in the enumerator manual document that we have developed for data collection and estimation of respective subindicators. Now in any case, using the more sophisticated approach, what do we need information on is the value of output. Now in terms of the value of output, what does it mean? It includes total farm cash receipts plus direct program payments, if any, by the government plus income and kind of the holding, if any, plus change in inventory. It could either be positive or negative. So value of output, what does it include? It includes the same variables or data items that is the physical quantities and the farm get prices of crops, livestock and other farm activities or products. So this remains the same. We need not to have additional questions for us to collect information, but the information which I showed you for the productivity indicator is sufficient for us to have information on this. Now additional information, if it is available, then the country should use it to and adopt the more sophisticated approach for calculation of the indicator, direct program payments, income and kind and value of inventory change. So this is the additional information. This information already exists because we need this for farm output value per hectare as well or land productivity indicator. Another important aspect or crucial variable which for us is needed to calculate the net farm income using sophisticated approaches, the cost, the cost of production or the cost of running the agriculture operations. So it includes both operating plus fix plus depreciation. So in case of operating expenses, what does it include? It includes labor expenses, fertilizer expenses, pesticides, fuel, electricity, cost for feeding animal if it is a livestock farm, irrigation costs, taxes, depreciation charges and others. So costing will include all these variables. It could be rent, it could be many other things. So we need total value of output. We need cost of producing the total value of output and using a simple formula whereby we subtract the total cost from total output. We estimate the net farm income for that particular agriculture holding for that particular year. Now as I mentioned, not always such detailed level information exists. So in this case we offer two staggered simplified options. So the first simplified option is we collect output quantity and farm grid prices for crops and livestock products and byproducts. But in this case we still have to collect information on operating expenses, input quantities and its market prices and output quantity and farm grid prices of the other on-farm activities as well as input quantities and prices utilizing production of the other on-farm products. In this simplified option, which falls between the third and the first one, we exclude depreciation and value of inventory change. So in this case we don't consider these two variables. Even if this information is hard to collect or costly to collect, then we offer a third solution, which has been tested in Bangladesh as well, whereby we respond directly about his declaration of agriculture holding profitability over the last three calendar years. And this simplified option too is part and parcel of the SEG indicator survey questionnaire or survey model which I've been talking about throughout. So we ask the farmer a simple question or we collect information on all these variables which I just explained. And we ask him as to whether he was profitable in the last three years or whether he was profitable in how many years he was profitable in the last three years. So whether he was profitable in one, two or three or none of the past three consecutive years. And depending on his answer, we then assign the green, yellow and red status to the agricultural holding and the agricultural land area that it's managing owning or operating. So the holding is classified as green or desirable if the profitability is above zero for all past three consecutive years. The holding is classified as yellow if the profitability is above zero for at least one of the past three consecutive years. And the holding is classified as red if its profitability is below zero for all three past consecutive years. And based on the answer given to the question, we then assign the statuses to the agricultural holdings. And by virtue of that, we assign the same statuses to the agricultural land area that that particular holding is managing owning or operating within aggregate all the areas or all the agricultural holdings that are classified as green, yellows and red. And we divide it by the nationally representative agricultural land area collected using the same agriculture survey for us to estimate this percentage. So let me let me now give you an hour view. But before going there, so you may you may ask me as to why we have selected three years instead of two or one or why not more years, right? Now again, the selection of three years was arbitrary. This was a consensus reached with the experts both in-house at FAO and outside experts, which include country institutions as well. So it was not that FAO was developing the methodology of SD2 for one in isolation. And every step of the way we were we were involving key stakeholders at the national level for us to make sure that the methodology is then owned by the countries. So the selection of three years recall or reference period is to make adequate assessment of farm profitability over an extended period to account for a bad year due to market failure, that is low prices of outputs or high prices of inputs in a certain year or negative agroecological or environmental factors that may have negatively impacted the farm profitability, that is heavy or untimely rains, floods or pest attacks. So to account for all these different external events, which are beyond the control of the agriculture holder or the holder of the agricultural holding, we are asking about the profitability for three years, not one year, okay? Obviously, if the holding is not making any profit in the past three years, this means that it shouldn't be in the business of running farming operations in first place. Obviously, the holding is not able to generate sufficient resources that can support the livelihoods of its holder. So I stop here, let me just share my screen with you, we still have eight minutes. I'm going to show you the exit sheet now. So in terms of data collection and then analysis of this particular sub indicator, I mentioned to you that we are adopting different approaches and based on the information existing at the country level, the country may pick and choose which option is best for them. As I mentioned to you earlier, the question in the 241 survey module is how often was this holding profitable? Of course, then the concept of profitability is explained to the farmer or to the respondent whereby we say profitable means that the value of production was greater than a total cost, either fixed or variable. And then based on the question asked, the reference period is last three calendar year, obviously, the farmer may say that I was unprofitable for all three years, profitable in one out of three years, profitable in two out of three years, profitable in three out of three years. And depending on the answer to this question, we then directly assign the farm and its agricultural land area, green yellow and red statuses. Now, in terms of more sophisticated approaches, I was mentioning to you earlier, some information has already been collected for in the context of profitability indicator. So we need not to re-ask this question to the farmer, those questions are sufficient. So what we need information on is total value of crops, total value of livestock, total value of other on farm production activities. So this will give us the total value of everything that is produced on the holding. What else do we need information on is the cost to produce the crops and livestock and its products and byproducts. And as I mentioned, these crops, these inputs can be collected using a very sophisticated approach asking maybe five or six questions. But this is just a summary table whereby we say that apart from the total value of output, we need information on cost, that is wages, labor and kind, fertilizer, pesticide, fuel, electricity, feeding animal, irrigation, taxes, depreciation charges, others. And once this information is collected, we have sufficient information for us to estimate the profitability of the agricultural land. So all we need to do then is to subtract from the total value of output the total cost for us to estimate the profitability. Now in case of the simplified option, the analysis is straightforward. So the simplified option is only recommended if the first two options are not feasible or if the agricultural survey is not extensive enough for it to have all these questions about the revenues and the cost. So in this case, the country can add just one question, which I just explained, right? So we asked the holding as to whether it was profitable and this holding replied I was profitable in two out of three years. And based on the threshold, as you can see, this holding will be classified as yellow because its net farm income is above zero for at least one of the past three consecutive years. And so on, profitable in three out of three years, another holding, desirable, not unprofitable in all three years, unsustainable, and so on. And as I mentioned, so once we assign the sustainability statuses to the agriculture holding, by virtue of that, using the same logic, we assign the same status to the agricultural land area of that particular holding. So in this case, holding one has nine hectares, so nine hectares become yellow and so on. We then add up the yellows, greens and reds, and then we divide by the nationally representative agricultural land area to estimate these proportions. Now the sophisticated option, so this was a simple option, right? Just one question, get declaration from the farmer, do direct assessment, it's easy. The sophisticated option, as I just explained, is a bit complicated. So you need to collect information on all the output value, which was shown to you in a question here, which has already been collected for the land productivity indicator, so you cannot avoid that. So one side of the equation is already covered. What else you need to collect information on is, which I just explained to you, is the cost of producing all those outputs, right? But then you need both the production and the cost collected periodically every year. So you need all these questions, the three questions which I explained to you earlier, plus the costing of those questions collected every year. For you to estimate the farm profitability every year. So in a year first, the total value of output was 1200, direct program permit source 170, income and kind was 100, value of inventory change was 30 and so on. So you estimate that using the sophisticated approach for each year. You estimate the cost each year for the past three consecutive year. And then you estimate the profitability as to whether this holding was profitable and in how many years, out of three. And then we use the same logic to assign the agricultural holdings and the agricultural land area, sustainability statuses. And lastly, we use the same formula whereby we add up the areas classified as greens, yellows and reds. We divide by national representative agriculture area to calculate these proportions. So I will stop here now just to reiterate. The sophisticated approach is more data demanding because you need to collect information on all the outputs, all the costs for each year. Which in terms of questions in a survey is too much. And hence we recommend to countries to use this simplified option. Which is instead of asking information about all the costs and the outputs asked directly to the farmer about his declaration of holding profitability in the last three years. So I stop here. Okay, Asfanya, do you have time to take questions or not? Yes, maybe five more minutes. Okay. So for the moment we have one question. So how to estimate on land, parcel or plot? Look, for us, both are fine. Okay, so plot and parcels both are fine. But it will be good for you to have estimates at plot level. But we don't discriminate. I mean, if you're collecting parcel level information, that is fine. If you're collecting plot level information, that is fine. The only thing is that you need to basically comply with the land use classes that we are recommending countries to follow. So what I mean by that is we shouldn't be including or excluding the land use classes which defines agricultural land area. So we should stick to the one that defined agricultural land area as defined by CFF and WCA 2020. Okay, another question. Is poultry included in the calculation? Poultry, of course, will be part of the livestock because it's in the livestock sector. So basically, yes, it would be if it is major subsector, livestock subsector for the country. And as part of the sample, yes, it would be. Okay, I think we finish the questions. So just one note from my side. I apologize. I realize that the panelists cannot use the Q&A section. They can only see the questions. So I apologize. That's okay. So for the panelists, they can still use the chat while for the attendees. Please keep using the Q&A section. Asfandjar, we have finished the question. We are sharp on time. I think so we can now close it. Of course, any question that you might want to answer, they have to ask about this first part will be welcome tomorrow. And that's it. So let me open my video just to close this session for today. Thank you again for having participated. And we have already started quite intensely. We have covered only two subindicators, but that's fine. We have time the next days to cover all the rest. So thanks, Asfandjar. Thanks, Thomas again. And see you tomorrow sharp. We will start sharp. And see you again tomorrow. Thank you. Bye-bye. Thank you everybody. Bye-bye. Thank you. Thank you. Bye. See you tomorrow. Thank you. Thank you. Bye-bye. See you tomorrow.