 Good day. So this is the final session in a series of videos on the Zambian tax benefit micro simulation model micro Zamod and in this session, we're simply going to be going through the model and looking at all of the policies in detail So we've before we start off and we have our main user interface and Just to repeat some of the things that we've been through already At the top of our user interface. We have our seven tabs Which each open up to reveal a ribbon menu So if we go to our first Our second tab rather which is display We don't really use much of these other functions, although a handy one to use Especially when one is making reforms and adding new policies to the model is automatic conditional formatting as this highlights The differences between the base system and the reform system. So this is quite a handy one to use We then have our country tools tab, which we've already looked at in our previous sessions And here we can use this tab to add a system or delete a system In our country tools tab, we also have our operating indices which specify Our operating factors for our data And we don't really use any of the other Tools in this country tools tab We then have our administration tools tab and one Tool that we use here that we haven't spoken about before is our variable to tools. So I'll just Look at that quite briefly So if we click on variables and this is quite a handy tool to use together with the DRD As this specifies all the variables that Have been used in the model and in addition has any other variables that one might want to add when Creating a new policy or reforming an existing policy So in addition with these with this variables tool, we can also add new variables That we want to the model as long as they Conform to the Euromod naming convention so we can we have a list of acronyms here Which we've spoken about briefly and within these lists. There are various other Variables so we can use this tool to add new variables that we don't have in our model that we might want to use Or we could use this tool to check To check the naming conventions of the various variables that we want to use So that's our variables tool We don't really use the add-ons tab Applications, which I'll look at towards the end of the session. We have two main Features of this tool that we use which are the stats presenter and the open output file which opens our output onto an Excel file and I'll speak more about these when we actually use them towards the end of the session and then we have our help an info tab, which is just like any other ordinary help program and Also specifies the version of our model that we're using which in this case is version 2.0.5 Okay, so now to walk through the model So we've already been through some of these policies in the in quite a bit of detail So I won't spend too much time on them, but the ones that we haven't looked at I'll spend a bit of time on them so our first policy is our upgrade policy and as you will remember this policy is made up of one function, which is called upgrade and this the purpose of this function is to upgrade our Data set to bring it up to date with inflation So we as we mentioned our data set is the 2010 living conditions monitoring survey and the default factor that we use as the overall CPI and then we've also specified an earnings inflator inflator to upgrade earnings and self-employment earnings as well so and We've also specified our inflators our operating in inflators for CPI for food items and we also have our CPI non-food inflator for non-food items So that's our operating policy our next policy which is a Definitional policy as you'll remember is our income concepts or income lists So I wouldn't spend too much time on this policy as we have looked at it in quite a lot of detail in our previous session but just to To remind you that an income policy an income concept or income list rather is an aggregate of Several variables that is added to produce that income list So if we look for example At our first income list, which is I L underscore taxably a one we see that this His income list is made up of several several variables such as income from employment income from self-employment employment income from pension income from property and The list goes on and most just to reiterate from our previous session within our income concepts or income list we now have a Several new income lists which we need to add to if we have a reform scenario For one of these categories in order for the stats presented to work so if you remember in our previous session we had a Child reform universal child reform or universal child benefit rather and we needed to add we needed to add that to our income lists For child benefits in the stats presenter in order for the stats presenter to work So just to take note of the new income lists that we now have because of our stats presenter and also to reiterate that we can only add To one of these income lists in order for the stats presenter to work our next policy Which is also a definitional policy is our tax units or assessment units. So we've already been through this Policy and as you can see this policy is made up of the three functions and if we open the first one up Which defines the household? We see here that this policy is made up this function rather is made up of five parameters in which we stipulate the name of the tax unit the type the dependent child condition and the assigning of dependent Children and the assigning of dependent partners So that's our tax unit Next we have our constants policy, which is also another definitional policy and we've been through this in quite a bit of detail But just to remind you that our constants policy is where we have where we specify amounts Thresholds rates Our poverty lines are also specified here, which I hadn't mentioned before So here we have Our severe poverty line and our moderate poverty line which are specified in our constants policy And in 2015 we can see that the severe poverty line was a hundred and fifty two While the moderate poverty line in 2015 was two hundred and four and fourteen so That's our constants policy where we just have our amounts our Any rates that we have that we use in the model our poverty lines are upper limits for our turn turnover tax and Any amounts that we assign for benefits So our next Policy that I haven't spoken about before are our poverty lines. So this policy is an income Policy and it's called poverty underscore lines underscore ZM and As you can see this policy is made up of two functions, which are two arithops So we have our severe poverty line and most importantly to note with this we can only Use one poverty line at any one time. So as you can see see our moderate poverty line is Currently off because our severe poverty line is on So this is What is used in the poverty calculations for the stats presenter and We can see that the formula that is used is simply our poverty line that is specified in our constants Which is in 2015 152 the output variable produced is simply SPL and the tax unit is then is the individual so As I mentioned in order for the stats presenter to work only one of these poverty lines can be searched on at any one time So that's our poverty line policy We then are we then have our employee pension contributions so All employees and wage employment are liable to pay a pension contribution that is calculated at 5% of gross salary So we see that this Policy is made up of one function, which is a bend calc and in turn this bend calc is made up of Five parameters So we have our comp underscore conned Which is an in essence our eligibility Criteria, which in this case is Y em has to be greater than zero so income from employment has to be greater than zero and in order for someone to be liable to pay This pension contribution and then we have our comp underscore per tax unit, which is in essence our Formula to calculate the contribution which in this case is income from employment so em times by the This tiske p underscore rate, which is 5% And then we have our upper limit Which is specified at 796 Zambian quatcha per month So after this calculation is done, we have our output variable which is called tiske p underscore s and All of this is done at the level of the individual So that's our first social insurance contribution Policy, which is the employee pension contributions So similarly we then have our employer pension contributions, which will be Roughly the same as the employee pension contributions so our comp underscore conned is income from employment greater than zero and then our comp underscore per tax unit is income from employment times by the the rate which in this case is 0.05 and Again, we have an up a limit of 796 Zambian quatcha per month and our output variable in this instance is tscerpi underscore s and this is done again at the level of the individual so those are two Social insurance contributions for both the employee and the employer pension contributions So then we move on to our turnover tax policy and this is our first tax policy So we've already looked at this in quite a lot of detail in our earlier session. So just to reiterate our turnover tax policy is made up of one function one Ben calc and This is made up of in turn made up of four parameters So we have our comp underscore conned which is in essence our eligibility and this identifies individuals who must pay turnover tax And in this case individuals who are liable to pay turnover tax have to have an income from turnover that's greater than zero it's our first condition and That income from turnover has to be less than the upper limit for turnover tax, which in this case is 800,000 Zambian quatcha per month So that's our first parameter which in essence identifies individuals who must pay turnover tax We then have our second parameter, which is our comp underscore per tax unit Which will take our income from turnover tax and multiply it by 0.03 and I as I think I mentioned in the previous session This zero point zero three or this rate of three percent In practice should have been added to the constants policy as it is good Modeling practice to add all rates and amounts to this policy as opposed to putting them in the actual policy itself so now Once we've identified the individuals who must pay turnover tax and we've specified the rate at which they must pay Tax on on turnover on their turnover We then have our output variable which is called TT and underscore s and all of this is done at the level of the individual So that's our turnover tax policy We then have our income tax policy Which is made up of two bin calcs Which are in turn made up of four parameters So first parameter, which is our comp underscore cond Which is in essence our eligibility criteria is simply TTN underscore s is equal to zero and if we go back to our previous Policy, which is our turnover tax policy. We see that this output variable Called TTN underscore s is the one generated from people who are liable to pay turnover tax. So if this output variable if this TTN underscore s is equal to zero Effectively meaning that people that these individuals are not liable to pay turnover tax then The comp underscore per tax unit is ill underscore taxably or one And if we go back to our income lists or income concepts We'll see that ill underscore tax ill underscore tax will be tax ill underscore taxably or one Is taxable income Used in income tax policy where no turnover tax is paid So that's our comp underscore per tax unit. We then have our output variable which will be TTB underscore s and this will be our tax base that we use in our shared calc Function and all of this is done at the level of the individual So that's our first Ben calc in our income tax policy We then have our second Ben calc Which is Again made up of four parameters. So the first parameter is our comp underscore cond And if we look at our comp underscore cond again, it takes the Output variable from our turnover tax policy, which is TTN underscore s and if this is greater than then zero In other words, if these people Are liable to pay a turnover tax then the comp underscore per tax unit is called ill taxably zero two And if we go again go back to our income concepts and look at so that will be our second income lists and this is Our this income lists define The taxable income used in income tax policy where there is turnover tax So where individuals are liable to turn to pay turnover tax and then lastly if we look at our shared calc Function, which is our last function in our income tax policy So again, we've been through this In quite a bit of detail. So but just to reiterate that shared calc is designed to take a base amount and then calculate Apply certain tax bans to to that base amount or to that income So in this case, we have our base amount, which is called TTB underscore s, which we've we generated from this previous Ben calc and then we apply a schedule of bans in order to calculate The overall income tax which is then outputted to this variable called TIN underscore s And this is all done at the level of the individual So we then have another social insurance contribution called the medical levy levy, but as this was only Was abolished after 2010 I won't be going through this policy, but we have modeled it for 2010 But it was discontinued after that So now we can go to our first Benefit, which is the social cash transfer for rural areas So just to reiterate from our previous session. This benefit is made up of This benefit policy is made up of 16 functions So we have our first function, which is our DEFAR, which just specifies for intermediate Intermediary variables that we're going to be using in the model So we've got our I underscore rule underscore 12m We've got I underscore rule underscore fit underscore for underscore work And then we've got I underscore rule underscore live underscore score And then our last intermediate variable is our I underscore rule underscore live underscore score underscore scaled So that's our first function. We then have our first LH function, which we've been through Which basically determines whether or not an individual is from a rural area and Whether or not the individual is the head of the household. We have our DHH is equal to one Which is our demographic Variable indicating that the individual is the head of the household and We have our DSD is equal to one indicating that the individual has been in the same district for a period of 12 months or more and We have our DRU, which is equal to zero Which is a flag to Indicate whether the household is a rural household or an urban household So in the case of the urban of the social cash transfer for urban areas This DRU is equal to one and we can look at that Here So that's our first eligibility condition, which we've seen before in our previous session Our next eligibility condition is our foot forward ratio test and in this Eligibility function is made up of three parameters Which is our LH underscore conned and in this Parameter we're looking at two criteria. We're looking at whether or not the individual is the head of the household so if DHH is equal to one That means that they're the head of the household and then we're looking at whether or not the individual Passes the foot forward ratio test so if D if I is equal to one It means that the individual has Passed the fit for work ratio test in other words, they're not fit for work or they have Members in the household so then we have Output variable which is generated which is one of our intermediate Variables which is called I underscore rule underscore fit underscore for underscore for work And then our tax unit, which is the individual level So then we have a series of 12 Ben calcs So I won't be going through all of these Ben calcs In detail because they the methodology behind them is is essentially the same So I'll go through the highest level of education in the household So what this Ben calc is essentially trying to do is we're trying to generate a score based on the highest level of education in the household so we have Depending on the highest level of education we have we assign a score Ranging from minus 400 minus 542 to a positive 511 so if DHA D E H 0 1 is equal to 0 this variable is Telling us that an individual only has no highest No education at all So if DH D E H 0 1 is equal to 0 this individual has no Education at all and they are assigned the score of minus 542 however, if D E H 0 1 is equal to 1 This means that this individual has an Level of education of between grade 1 and 3 So then if they have this level of education between grade 1 and 3 we then assign them a score of minus minus 364 and Then in a similar fashion if D E H 0 1 is equal to 2 It means that this individual has a level of education of between grades 4 and 6 So then we would assign them a score of minus 223 and Then again if D E H 0 1 is equal to 3 it means the individual has a level of education of grade 7 And in this case we would assign them a score of minus 70 and then if D E H 0 1 is equal to 4 It means that this individual has a level of education of between grade 8 and 9 and in this case We would assign them a score of 95 and then again if D E H 0 1 is equal to 5 it means that this Individual has a level of education of between grades 10 and 12 and in this case we would assign Them a score of 280 and the last one which is D E H 0 1 equal to 6 it means that the Individual has a level of education or the highest level of education is above grade 12 So they will be assigned the highest score, which is 5 11 so Each individual is assigned one of these scores depending on the level of the highest level of education that they have and then We generate an output variable called I underscore rule underscore live underscore score and all of this is done at the level of the individual So what happens? Is that we do this for a number of categories? So if I open up one of the other Ben calcs, we can see that we have a toilet category and again depending on the type of toilet that The household has we Assigned them a score in this case for the toilet Assigned them a score ranging from minus 348 to 3 to a positive 336 if they have a toilet with a slab and flush So we do this for a number of categories and most importantly what happens is that every time we add Something to our underscore rule underscore live underscore score. We use output add var We use so we use output underscore add underscore var to indicate that we are it's Incremental so we're adding The score from the highest level of education and then we add the toilet category score and the roof material score and so on and so forth So all of this is done To generate the living conditions index Which is an essence a kind of a proxy means test So we do this for a number of categories as you can see we've got energy for lighting energy for cooking Asset ownership in terms of a mattress sofa TV o'clock and electric iron So we perform this Ben calc several times and each time again, this is output this Score is is is output advar Indicating that it's being added to the previous scores and the the name of the the the variable The output advar variable is I underscore rule underscore live underscore score so then After all the Ben calcs we then have the one arrow top function in this policy Which is to simply scale the score to make it range between zero and one thousand and we've seen this Arethop in the previous session So we simply take our output variable, which is our underscore rule underscore live underscore score Which is an aggregate of all these? categories and we add 1854 and divided by six point nine zero four and this is simply to make it range between zero and one thousand And then the output variable in this case is called I underscore rule underscore live underscore score underscore scaled and all of this is done at the level of the individual So then we have our final Ben calc now, which brings together all of our eligibility conditions for the rural For rural areas So if you'll remember our previous eligibility conditions The individual had to be the head of the household and they had to be in a rural area for 12 months or more So I underscore rule underscore 12 m is equal to one and they had to Pass the fit for work ratio test And in addition In order to be eligible to get now to now get the social cash transfer amount The I underscore rule underscore live underscore score underscore scaled which we generated in this Previous Arethop has to be less than 460. So that's the threshold for rural areas and If an individual fulfills all of these eligibility criteria for rural areas, they then allocated the BSA amount Which is 70 quattro per month And then the output variable that is generated is called BSA underscore S And all of this is done at the level of the individual and then There's an additional social cash transfer payment for households containing one or more disabled people so again in order to receive this amount you have to fulfill the previous criteria which we've specified so The individual has to be the head of the household and They have to be in receipt of the social cash transfer amount meaning that they have had to fulfill the other conditions that we specified earlier and additionally they have to have One or more disabled people in in the household and Then if and the household lastly has to be in a rural area. So DRU has to equal to zero So when all of this is fulfilled Then the comp underscore per tax unit will now be called BSA underscore disabled underscore amount and that is the amount that they'll receive Which is 70 quattro per month and this again is output add VOD, which means it's added to the previous To the previous amount to the standard social Should to the first social cash transfer amount this is added because there's a Disabled person in the household one or more disabled people in the household and again. This is all done at the level of the individual so that's our social cash transfer for rural areas and It'll be very similar except for a few differences for urban areas. So in terms of the eligibility criteria in this case The household has to Be in an urban area So DRU won't equal zero in this case. It'll equal one indicating that the household is in an urban area and Again additionally for our second eligibility. There's another fit forward ratio test and there's a disability requirement for this For the social cash transfer in urban areas So then again, we'll have the various categories that we use to calculate our living conditions index and some of these will be slightly different because We're now looking at urban households, so we've got In this case, we've got asset ownership in the form of a computer a sofa a table a bed an electric iron So but again, we will do the similar process To scale the live score to make a range between zero and one thousand and Again, we'll use a similar process to assess Eligibility the final benefit calculated to assess eligibility and the urban threshold in this case is 644 As opposed to 460 in the rural areas and then we will assign them the standard monthly social cash transfer amount which is 70 quattro per month and Again, this would be output advard and the Variable we call BSA underscore S and Again, this will be allocated to the head of the house a household as previously defined in our eligibility and Again, we'll have another additional payment for Households containing one or more disabled people which will be similar to the one we had in our in our Social cash transfer for rural areas so that's Those are two benefit policies We've looked at the social cash transfer for rural areas and the social cash transfer for urban areas We then have our next benefit, which is the homegrown school feeding program, which is currently not modeled But we hope to model this in the 2016 and 2017 Systems we then also have our farmer input support program, which is also currently not modeled hence both of these are off and and so our VAT policy is made up of one function, which is an arithop and This is made up of three parameters and this simply multiplies the income lists that contains the standard rate of rated items and multiplies it by the VAT rate, which is 16% So this I L underscore VAT underscore zero one Is our income list that contains our standard rated items and we multiply this by VAT by our VAT rate to give us our amount paid in VAT, which is our TVA underscore S and this is done at the level of the household So then we have our excise duty and VAT on excise duty items, which is slightly more complicated as We first have a number of different excise items Which we first have to calculate excise duties on and then we add VAT on on those excise items, so I won't go into too much detail with this one, but just to briefly Explain what's what's being done here. So then we have our last Definitional policy, which is our standard output at the individual level and we've already looked at this But just to reiterate that We have all our output at the individual level and The asterisks next to the different variable groups simply means that all Variables beginning with ID beginning with S beginning with D beginning with L will be outputted So it's basically it's just a wild card to indicate that everything All these variables beginning with these letters will be outputted to our output file So that is our model In a nutshell I'll now go on to our Applications to show you first of all Our output file and then second of all the stats presenter So if we open our output file We can choose The system that we want to look at so this open output file Enables us to check within the data set the variables that we have Simulated and also the variables that are within the actual data So we have a complete complete list of all the variables in the file and their corresponding values So you if you look at the variable DAG, which is age, you'll see that we have a complete list of Of the variable first of all of the variables and then the the values for those variables So this is a good way, especially if you want to check if you've Performed a Reform scenario if you've modeled a reform scenario in the model and you want to check that it's worked this Excel output file is a good way to check That your reform has done what it was intended to do because it's got a full list of all the the variables That we've simulated including all our intermediate intermediate variables. So that's our open output file We then have the stats presenter which is a fairly new addition to Euromod and Microzamod in that sense And so if you go to stats presenter and You click on that you presented with this dialog box, which will ask you if you just want to do South Mods Statistics or comparison. So in this case, we're just going to look at doing South Mod statistics And if we click on okay, it'll ask us Which system we want to look at so we can click on 2015 and It'll then ask us Whether we want to look at consumption based or income based Statistics so we can just Choose consumption and click on okay So once it's done performing its calculations Again within given a series of information which can fall under three broad Categories or tabs. We've got information on text tax benefit policies poverty and inequality And if we briefly look at the information on tax benefit policies, we can see that we've got Information on government revenue through taxes social insurance contributions and indirect taxes so We've then got information on government expend expenditure on social transfers And as we can see the only government expenditure on social transfers is on social assistance and this is 358 Million quattro because this is in yearly million in the national currency So if we go over to our poverty tab We can then see a Number of poverty statistics such as the share of poor population in percentage Which is currently at 47.1 percent in 2015 and then we can then again look at this and for the different groups such as male headed household Male headed households female headed households households with children households with older persons We've then got measures of the poverty gap The average normalized poverty gap and again, we've got a figure for the whole population and then again, we can look at it in terms of male headed households female headed households households with children and households with older persons and Then we've also got the absolute national poverty line and The last tab we can look at is our inequality tab, which also has a number of inequality Statistics such as our Gini coefficient Which is 0.5 to 6 0 in 2015 we've then Got our P 80 in P 20 ratio and We can then look at the quantiles of distribution and the median of Inequality and then we've also again got our absolute national poverty line so the stats presenters quite a handy tool to do to Calculate the effect of poverty and inequality and if you do a comparison which would be If perhaps you've implemented a reform scenario then you can do a comparison from maybe the base year to the reform year and see The impact of your reform on all of these three tabs so on the tax and benefit policy on the poverty and on the inequality and You can also export these statistics or you can export all of them or group or a selected table for further analysis into You can export them to to excel for further analysis using a different statistical package for example so that's Or on the stats presenter and that brings us to the end of this session and thank you very much