export growth and poverty, macroabc model with poverty module · macroabc model with poverty module...

Macroabc model with poverty module

Micromacro Consultants

Export growth and poverty,


Dr. Marein L.J.H.A. van Schaaijk in co-operation with Drs. Bas van Tuijl

Scheveningen, The Netherlands, April 2003 The objective of this paper is to introduce a combination of a macro model and a poverty module and then demonstrate how to quantify the effects of combinations of macro and redistribution policies on the numbers below the poverty line and their net real income, taking an increased growth of exports in combination with lower tax rates as an example. This paper builds on the experience gained in macro model projects in and for Curaçao, Indonesia, Kenya, EU15, Suriname, the Netherlands, EU15, Poland and Ethiopia. We present the macroabc model ‘’Curalyse’’ with the poverty module ‘’Antiltax’’ of the small island of Curaçao and MicromacroSim Kenya as an example. For shareware model-files and multi-media slideshows explaining some of these macroabc models and the poverty module MicromacroSim we refer you to www.micromacroconsultants.com This paper can also be found on this webpage.

Table of Contents

Table of Contents 1

1. Introduction 2

2. Overview of a Macroabc model 3

3. MicromacroSim, poverty module to Macroabc model 10

4. How to run a simulation, some examples for Curaçao and Kenya 12 4.a The case of Curaçao 12 4.b. Same variant, Kenya 15

5. Concluding Remarks 17

Appendix : Sources and Literature 18

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1. Introduction GDP growth alone is not a guarantee to poverty reduction, but how to quantify the effects of macro policies in combination with redistribution policies on an easy way? The objective of this paper is to introduce and demonstrate how to quantify the effects of increased growth of exports on the numbers below the poverty line and their net real income, using a macro model with a poverty module as instruments. There are three factors that can influence the number and purchasing power of poor people in a country: 1) macro-economic growth, 2) income redistribution by government, and 3) policies directly affecting the poor. In this paper we will combine factor 1 and 2 and concentrate on the effects on the income distribution of individuals The method we will introduce consists of a methodology that helps to translate macro-economic forecasts and developments into the effects of these developments on the amount of people under the poverty line and their net real income growth in future years. The macro-economic developments are obtained from a macro model that is based on the Macroabc methodology. The translation instrument is called the MicromacroSim methodology. Both methodologies are developed by Micromacro Consultants (MMC) and used in practice in many different countries in four different continents. After introducing Macroabc and MicromacroSim in the first two chapters we will give a demonstration in the fourth chapter where we will take Curaçao and Kenya as examples. This demonstration makes use of three steps, using the two mentioned models. 1. In the first step the Macroabc macro-economic model will be used to quantify the

effects of an (assumed) increase of export growth on macro economic variables like formal sector employment, wage rate, consumer prices, unemployment and/or informal sector labor force, government deficit, etc..

2. In the second step assumptions will be made about how the government will spend the additional tax income (that is the result of the rise in exports) in tax reductions and possible other policies geared to improve the purchasing power of the poor.

3. In the third step the poverty module (MicromacroSim) will be used to translate the macro developments from step 1 and micro redistribution policies (taxes and allowances) into net real income growth for different groups in society and decrease of the numbers below the poverty line.

In this paper we will take the small island Curaçao as an example to demonstrate how to link macro-economic and micro poverty analysis. The Curalyse model for Curaçao and the accompanying MicromacroSim module Antiltax are available on the internet on the home page of the DEZ Curaçao www.curacao-gov.an. For the second variant we will use the MicromacroSim demonstration version which is based on Kenyan statistical data . The paper concludes with a discussion of strengths and weaknesses of the chosen approach.

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2. Overview of a Macroabc model In this chapter we present an overview of the Macroabc model methodology. We will start with an introduction of the Curalyse macro model of Curaçao that will function as an example throughout this chapter. Occasionally references to the KTMM Macroabc model of Kenya will be used for this purpose. Curalyse The macroeconomic model Curalyse is an aggregate supply /aggregate demand macro model for a market economy. It describes the behavior of market actors. The model consists of equations for both the demand side and the supply side. It is a simultaneous model that runs in the spreadsheet program Excel. The model is demand driven in the short run, with multiplier effects through consumption and investment. In the long run the competitiveness of the export sector explains the growth of production. High demand leads to low unemployment rates, however, low unemployment rates lead to wage and price increases. (In Macroabc models for countries where labor is abundant the role of unemployment rates is less important. However in those models the role of the capacity utilization rate is more important). High wages will result in domestic inflation which will decrease export competitiveness, causing a reduction in exports and a subsequent decrease of investments. Consequently, the model has a tendency to return to equilibrium with ‘normal’ unemployment (and capacity utilization) rates in the medium and long run1. Thus, the main feedback mechanism in the real economy works through the wage-price spiral. For instance, an increase in aggregate demand raises labor demand, reduces the unemployment rate, that raises wages and ultimately results in a wage–price spiral. The resulting inflation causes a reduction in competitiveness and a decrease of exports. The drop in exports and investment reduces aggregate demand until equilibrium is restored. The Curalyse model is used at Economic Affairs in Curaçao to monitor the economy and to analyze the effects of economic developments on the government budget as well as the other way around: the effects of government policy on the economy. Macroabc Methodology: Data and consistency framework Design of the structure of the macro model: which data and definitions are needed? Similar to other Macroabc projects the Curalyse project started with discussions in the country involved resulting in a merge of existing local expertise with macro modeling and MMC’s Macroabc methodology. During these discussions the different ideas converge and agreement is reached upon a draft theoretical base and data needs. In the following step by step approach the theoretical ideas and available data are brought in a draft consistency framework. In the final stage theory and data are used in regression analysis, with as output preliminary values of the regression coefficients in the model equations.

1 The theoretical base of the model is described fully in the sheet Theory of the model. Another sheet in the model provides the Manual.

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Furthermore in the Curalyse project it was agreed in the starting stage that the new model had to be very accessible, easy to handle and as compact as possible. However, since the model is a macro model and describes the economy as a whole, it has to be comprehensive, allowing a consistent view of the macro economy of the country. At the start of the Curalyse project the Curaçao SNA was still based on the old SNA (1968) system2. This SNA describes the goods and services transactions (private consumption plus government consumption plus private investments plus government investments plus exports minus imports gives GDP). However, information concerning prices, the labor market and monetary variables is not included in this system of National Accounts. The same is true for stock variables like the government debt and the foreign reserve stock. However, thanks to the statistics of the CBS, the Finance Department, Economic Affairs and the Central Bank, additional information is available. We used this as input to construct the consistency framework for the macro model. In fact this framework is rather close to the new SNA3. Actually the Macroabc approach combines two worlds, the supply (the data that are available) and the demand side (the data a macro model needs from a theoretical point of view) in a consistent macro database4. The possibility to construct a working macro model while the relevant statistics are in short supply is one of the strengths of the Macroabc methodology. Both the Macroabc consistency framework and the SNA93 approach need the following information in addition to the SNA68: • A distinguishing of institutional sectors. For the time being production and

consumption of households are taken together in the private sector, distinguishing between production and investment on the one hand (‘Businesses’) and savings and consumption on the other (‘Households’)

• The inclusion financial variables: information about the (net) capital account transactions of Foreign Sector and Government, the change in Money supply, exchange rate and interest rate

• Price mutations that are consistent with reported volume mutations • Inclusion of labor market variables, such as population, employment and wages. If

relevant including a division into a formal, informal and traditional sector • Information to make the difference between flow and stock variables explicit • The presentation of the statistical differences between the different sources • Besides information about the country involved, the model also needs input about

developments in the rest of the world (world trade, world inflation) The underlying idea of this Macroabc consistency framework was that it also might help the Statistical Bureau in a country to improve the analysis and presentation of its data. 2 In 2003 the CBS of Curaçao will publish National Accounts in SNA93 format. The Macroabc models of Kenya an Indonesia are also based on the old National Accounts, the Macroabc-NL for the Netherlands (as shareware on www.micromacroconsultants.com has been based already on SNA93 format. 3 See ''System of National Accounts 1993" by UN, EU, IMF, OECD, World Bank 4 Actually, because the Macroabc methodology integrates the accounting and modeling in one system, a special chapter (VIID) was devoted to this approach in: United Nations, New York, 2002, “Handbook of National Accounting”, Studies in methods Series F No. 81, New York 2002, Chapter VIID “Integration of accounting and modeling in the Caribbean: the ‘Antillyse’ model and the National accounts of the Netherlands Antilles by Runy Calmera, Marein van Schaaijk and Jan van Tongeren.

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Actually last year the CBS of Curaçao adopted the data part of the Curalyse model and in January 2003 it produced the Curalyse Source sheet that provides a consistent dataset. The macro data in several systems: statistical discrepancies It is very important to realize, that macroeconomic variables are interrelated. For example: GDP = E - M +C +I; Profits = added value enterprises minus wage bill; Budget deficit = Expenditures minus revenues; Saving = Disposable income minus consumption; Value = volume * price; given the values for wage bill and employment, the wage rate can be derived by definition; given the starting level of an index, and % changes of the variable the values of that index are given; given de starting value of a stock variable and its yearly changes, the levels of the stock for other years are given. In the model we want to avoid the presence of different values for the same variable in the same year, explicitly nor implicitly. However it is also important to be able to communicate with both the Statistics Bureau and the Central Bank even if their statistics present different values for approximately the same variables. Actually, while constructing a macro consistency framework for a country, we are confronted with many cases in which we find different values for (in principle) the same variable. We can distinguish different systems of base information, that are consistent within each group, but not between the groups: • Uses and Resources table in the SNA, current and constant prices • Balance of Payments on a cash basis published by the Central Bank • Government Fiscal Statistics (detailed revenue and expenditure of the government) • Price statistics In the macro consistency framework we use the SNA as the starting point. The next step is to make all subsystems consistent by introducing ‘statistical discrepancy’ variables that give the SNA value of a variable minus its value in another subsystem. (In the case of Curaçao this is not needed anymore because nowadays the Statistic Bureau takes care of the whole data part of the model and consequently all data is consistent). Detailed government variables In most cases the Macroabc models are especially used for public policy analysis. To monitor and forecast government revenue and effects of police correctly the model needs government variables that give a detailed view. Therefore in Curalyse we used the same detailed information as is in the tables of the Finance Department (in the case of Curaçao even a breakdown to total and regional government). Furthermore the consistency framework in some countries also contains a translation between fiscal and calendar years. Data organization A huge amount of statistical information is needed to feed the model, recent realized figures as starting values of the forecasts as well as historical time series for estimation purposes. The accumulation of the data starts with forming a rough idea of the needed data, then as much data as possible is collected, after this a first analysis is made and irrelevant information is deleted, finally the remaining data is organized in blocks.

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Macroabc Methodology: Forecasting and equations In the previous part we explained how the consistency framework is formed in the Macroabc methodology. However, the Macroabc models combine a data model with a simulation model. In this simulation part certain equations are used to forecast the future developments of the different variables in the model. Primary and secondary variables In the model the equations used in forecasting are divided into four groups: Primary variables: 1. Endogenous behavioral 2. Endogenous semi-behavioral 3. Exogenous Secondary variables: 4. Definition variables (also called help or auxiliary variables) Values for the secondary variables can be derived directly or (via other secondary variables indirectly) from the primary variables. Actual values for the primary variables have to come from outside the model. Their actual realized values are input and come from statistical sources. Their future values have to be calculated by behavioral equations (private consumption, private investments, wage bill etc.) or have to come as input from outside the model (world market prices, international interest rate etc.). The latter are called exogenous variables. The semi-behavioral equations float between being endogenous and exogenous. Take care: a data model does not contain any (semi-) behavioral equations. Such a model only exists of input and definition variables. In this combined data and simulation model some variables have values coming from input for past years and resulting from (semi-) behavioral equations for future years. Semi-behavioral equations in the model The government can affect the level of revenue and expenditure by means of budget decisions. The degree of this influence differs per item. In case of foreign debt with interest obligations according to international interest levels, for example, the government can hardly, or not at all, influence the level of its interest payments. This is true for the short-term. In the long-run the government might influence its level of interest payments by means of debt repayments. On the other hand, tax rate is an example of a budget item that is within the field of government influence. An increasing tax rate results in higher government revenue in the short-run. Furthermore, tax revenues vary along with economic trends, unless government changes tax rates accordingly. Generally speaking, government revenue contains a large endogenous component that is difficult to determine exactly in advance. That is why budget figures for revenues are estimates. However, it is possible to determine government expenditure in advance by looking at the budget plan. In the process of Macroabc model construction we pay special attention to the equations for government variables. We made a clear distinction between those government

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variables that are sensitive to government policy and those that are outside the field of government influence. For example, an average tax rate and a tax base together determine the income tax revenue. In the case of no policy change (with the same tax rates) the estimated tax revenue will increase with an increasing tax base. The tax base can increase because of economic growth and inflation, among others. If the government decides to increase tax rates, the relevant equation in the model has to be adapted. Concluding, the semi-behavioral equations inhibit some assumptions about the behavior of the government. The ‘no policy change’ assumption is the most common in this respect. It is important to stress explicitly that this collection of assumptions only leads to a working hypothesis about the behavior of government. This working hypothesis allows us to make calculations for the future. After this the government can become aware of the macroeconomic consequences of continuing their current policy, and consequently it might decide to change policy in certain areas. The next step is to incorporate these new policy measures into the model before making a new run. The policy makers can then compare model results including their proposed policy change with those of no policy change. Analyzing the pros and contras of both scenarios, the policy makers might want to formulate a third policy and request a new model run. This iteration process gradually converges to the estimation of the Government Budget. In order to use the model in this way it has to become part of the budget cycle process. Which behavioral equations, what level of coefficients? For each of the equations (see the box below) we needed a selection of explaining variables and an estimation of the coefficients. This is done by an iterative process based on: 1. Economic theory 2. Estimation results 3. Coefficients from CPS Matrix (derived from Input-Output table) in cost price equations and import equation 4. Other studies (about the country involved and Macroabc models of other countries) 5. The simulation properties

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Box: List main behavioral equations in Curalyse, the Macroabc model for Curaçao Components of GDP: (lags not mentioned) 1. Consumption: changes with net disposable income (80% wages, 50% profits) (lags) 2. Private investments volume growth: flexible accelerator (weight 26%) and net profits 0,33*(profit rate

minus interest rate)*value invested capital 3. Export volume % change: 0,5*growth of number of tourists + 2,5* (world market price minus export

price) + 1* relevant world trade growth (lagged) 4. Import volume % growth: 1*real final demand growth, reweighted for import intensity - 0* (import

price minus consumption price) Prices: 5. Consumption price % change: 0,5* (wage rate minus trend in labor productivity) + 0,5*import price +

100% change in indirect tax pressure. 6. Export price % change: 0,4* wage costs + 0,3*import price + 0,3*competitors price + 0,2*real interest

rate +change in indirect tax pressure 7. Investment price % change: 0,6*(0,5* wage costs minus trend in labor productivity + 0,5*import

price + 0,4*international competitors price 8. Wage rate businesses: 1*consumer price (half year lag, minus 0,4*indirect taxes effect) +1*labor

productivity trend – 0,5* increase in unemployment rate –0,1* (level unemployment rate –5%) Employment 9. Employment businesses % change: +0,9* real production growth (reweighted to labor intensity that

differs for exports, consumption and investments) -0,4* real wages Monetary variables: 10. Interest rate: exogenous 11. Exchange rate: fixed rate of Antillian guilder to US$ since 1971 12. Money supply: increases with 1% +0,5*(monetary financing by government + balance of payments

surplus) Box: List main behavioral equations in Kenya Macroabc KTMM Components of GDP: (lags not mentioned) 1. Consumption: changes with disposable income (98% wages, 96% profits) (lags) 2. Private investments volume growth: flexible accelerator (weight 50%) and profits minus interest

(weight 50%) and crowding-in: 0,3*(1+2*GDP real growth) +0,4*(disposable profits income minus long interest rate*invested wealth)+0,3* public investment - 0,4*public investment five years lagged -0,06*change in credits.

3. Export volume % change: 2* (world market price minus export price) + 0,8* world trade growth (lagged) + 0,2* % change in investment/GDP rate

4. Import volume % growth: 1,3*real final demand growth - 0,6* (import price minus consumption price) Prices: 5. Consumption price % change: 0,7* wage costs + 0,3*import price + 100% change in indirect tax

pressure. 6. Export price % change: 0,4* wage costs + 0,3*import price + 0,3*competitors price + 0,2*real interest

rate +change in indirect tax pressure 7. Investment price % change: 0,5* wage costs + 0,5*import price + 0,4*(capacity utilisation rate -1) +

0,1* real interest rate (t-1) 8. Wage rate businesses: 5 + 0,8*consumer price +0,7*labour productivity trend + 0,4* increase pressure

direct (wage) tax rate + 2* increase wage employment businesses +(for the time being - 0,05*informal sector rate and -0,1 increase in informal sector rate)

Employment 9. Employment businesses % change: -0,4* real wages + 0,8* real GDP growth; Informal sector number

% change: For the time being we take: +0,6*population % growth -0,6* employment % growth Monetary variables: 10. Interest rate: changes with 0,1*(consumption price change minus inflation target (exogenous). 11. Exchange rate changes: +1,0*(domestic minus foreign % change in prices, five years moving average)

+0,3*(domestic minus foreign interest rates changes) 12. Money supply: increases with 0,9*Real GDP growth and 100% inflation target

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Macroabc Methodology: In Practice Macroabc macro models are available in MicroTSP, Eviews, SIMPC or simply in spreadsheet like Excel, because they are very powerful nowadays and can run simultaneous models too. Excel has the advantage that all calculations remain visible. It is always possible to check the results by looking at the different Excel formulas. The models are spread out over different sheets. In most sheets every column represents one year. An important sheet is sheet Source which contains the database. The second important sheet is the sheet that contains the actual model with links to sheet Source for data from the past and equations to predict future values. Because information in the model is organized to make it easy to use by specialists normally a sheet Output is included to present the results of the model to non-users. This output may consist of the following elements: • Overview of key variables • Selected Annual Economic Indicators • Detailed Revenues and expenditures as well for total as (in the Curaçao case) regional

governments for calendar years in the format of the GFS • Table of Uses and Resources in the format of CBS • Monetary Survey (consolidated accounts of the banking system) in the format of

Central Bank (not all details) • Institutional National Accounts for the sectors Enterprises, Government, Households

and Rest of the World (anticipating to SNA’93) • Monetary overview (from disposable incomes to liquidity creation) • Accounts for each of the institutional sectors • Balance of payments • Government finance • Labor market survey Next to these three sheets many other sheets are included to help the user. You can find the Curalyse model as shareware on www.curacao-gov.an to have a look for yourself. Economic Affairs brings an update on the Internet at least once a year. Macroabc Methodology: Possible Modules One of the advantages of building a macro-economic model in Excel is that it is easy to construct modules that are linked to this model. Several of such modules were developed while working with Macroabc models. One of those modules is MicromacroSim. This methodology uses macro-economic input from the Macroabc model and a selection of micro economic data to forecast the developments of poverty and purchasing power in the economy. The next chapter will describe this methodology.

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3. MicromacroSim, poverty module to Macroabc model In the light of the global interest in the reduction of poverty and the accompanying need for an instrument to measure the effects of macro-economic policy on poverty we developed the MicromacroSim methodology. This methodology is an auxiliary in the translation of macroeconomic forecasts and simulations into microeconomic information about the number of people below the poverty line and the purchasing power of different groups in society. This allows the user to analyze the effect of macroeconomic developments and policy on the poverty level. Furthermore the inclusion of information of the tax system makes it possible to calculate how a change in tax rates will influence the tax revenues. Next scheme gives an overview of the model (all input, calculations and output concern previous years, the running year as well as future years): INPUT:

From Macroabc model or statistics for the past and assumptions for the future - Data on gross wage income levels and numbers in the labor force for

o Employees private sector o Employees government sector o The informal sector, unemployed and/or traditional sector

- Consumer prices And on a micro-economic level

- A recent income distribution which makes a division into different sectors (private, government, informal, traditional, unemployed, retirees) and into a number of income classes within these sectors and gives the average income and the amount of people for each group.

- Information about the tax system, rates and brackets - If relevant, information about the social security system

Assumption concerning the level of one or more poverty lines

CALCULATIONS - Calculation of the gross - net – real income for X groups in the

society, defined on the bases of income and sector - Calculation of number below the poverty line - Calculation of total income and total tax revenue

OUTPUT

- Real net income growth for the average income earner in the private, government, informal and traditional sector

- Graphs that show the development of purchasing power for X different groups within society

- Numbers below the poverty line for the next five years

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The information concerning individuals in the different sectors and income classes is calculated from micro databases, resulting in X groups (X = sectors * income classes per sector). MicromacroSim uses macro-economic forecasts from a Macroabc model concerning average wage rates and amount of wage earners in the private and the government sector to calculate changes to numbers and income classes in future years, assuming that within a sector the distribution does not change. After this a gross-net calculation is made for each of the X groups in all the years in the analysis. Finally the future net income of each group is compared to the poverty line(s) using an interpolation technique. This makes it possible to calculate an impression of changes in the numbers below the poverty line over the years. Please note that MicromacroSim simulates the effects on the income distribution of individual wage (or income) earners, not of households. This is the weakness as well as the strength of the module. If you need to know the effects of macro-economic developments on the income of households a grouping in classes is impractical because individuals in one household can belong to different socio-economic and income classes. To analyze household income a dynamic micro-simulation approach is recommended. However, such models are more complicated and difficult to understand, so they are not practical in the policy preparation process in which all kind of people participate. However for the time being we assume that changes in the income distribution of wage earners will be more or less proportional to changes in the income distribution of households. This assumption holds as long as Macroabc/MicromacroSim is used to analyze macro economic policies, excluding policies that have different effects on households than on individuals (like children allowances). Actually one of our research items is to calculate what effects a general increase in wages or a switch from unemployed to employed in the same data base would have on the income distribution of households and also the income distribution of individuals. This might provide us with elasticities to translate the results of simulations in MicromacroSim concerning individuals to households. Many different simulations can be done with this program, it can be used to assess the effects on poverty, purchasing power and total amount of tax revenue of:

• Changes in the inflation rate • Changes in the income growth in different sectors (private, government, informal

and traditional) • Changes in the (un)employment rate • Tax reforms (indirect tax, income tax) • Adjustment of the poverty line • A combination of any of the above

Next to this the program can be used for a historical review of purchasing power and poverty. The charm of MicromacroSim is that it can be used for a broad range of political and economic analysis. Therefore the program can be applied to meet the needs of many

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different countries. Up till now the MicromacroSim has been adapted to function for different purposes in the following models:

1. The tax-model for Curaçao called Antiltax (downloadable on www.micromacroconsultants.com),

2. The Suritax model for Suriname (including a poverty module), 3. A program that MMC has built for the ministry of Education, Science and Culture

of the Netherlands, 4. A calculation sheet used for a research in the Dutch health sector, 5. The Bontax model for Bonaire and 6. MicromacroSimDemo, test version for Kenya, a demonstration version including

multi media slide show of the methodology is available as shareware on www.micromacroconsultants.com. For this version statistical data for Kenya were used as an example.

weakness Macroabc and MicromacroSim together provide an instrument to analyze and forecast the effects of macro-economic developments and macro policy as well as re-distributional policies. However, the effects of direct measures to decrease poverty, like for example micro-credits and food transfers, are not (yet) included. Simulations with MicromacroSim: see next chapter

4. How to run a simulation, some examples for Curaçao and Kenya In this chapter we first simulate an increase in exports and assess the effects on the economy5. The resulting higher economic growth will lead to a lower government deficit which is assumed to be used to lower tax rates. This exercise is done for Curaçao as well as for Kenya. 4.a The case of Curaçao Curaçao is a small island in the Caribbean that suffered from high government deficits. However, the government executed successfully austerity measures (including more or less voluntary departure of one third of civil servants thanks to golden handshakes: they received their wage a few years ahead without needing to work for the government) and started an outward oriented policy, resulting in economic growth.

5 Of course export growth does not come from heaven. On 28 March in Nairobi Dr. Karingi presented the effects calculated with the Kenya Macroabc model KTMM of an export growth scenario based on a policy package (stable monetary policy, low interest rates, change from government consumption to investments, lower corporate income tax, higher FDI etc.)

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In Curalyse we run (the Macroabc model of Curaçao) a variant in which exports are increased with 5 % yearly in 2003-2006 and compared to a technical base line for 2003-2006 from Curalyse in which export growth is moderate. The results in Curalyse are an increase of the economic growth and a surplus in government finance. In a second run we decrease the income tax with the amount of that additional government surplus. The resulting key figures in this second run are shown in next table. Table Key figures Curalyse in deviation of base line Key figures for Curacao 2003 2004 2005 2006Prices, % change per year export price 0 1 1 1wage rate business 1 2 2 2consumption price 1 1 1 1quantities, % change per year Exports 4 4 3 3Imports 4 4 4 4private consumption 3 4 4 4investments by enterprises 5 6 5 5real gross domestic product 3 3 3 3employment of enterprises 3 3 3 2number*1000 number of unemployed -1 -2 -3 -3value in millions Naf foreign reserve stock 17 37 59 90Money 7 11 12 9Ratios unemployment rate % -2 -4 -5 -7profit rate 1 1 2 2budget deficit in % of GDP 0 0 0 0 After this the relevant Curalyse results (wage rates, numbers of (un)employed and inflation) are brought as input in Antiltax, and a first run with Antiltax is made. The resulting output in deviation of the base line in Antiltax is presented in the next table: Table: Output Antiltax Purchasing power abstract 2003 2004 2005 2006 in deviation of base line Average wage earner businesses 0,4 0,7 0,8 0,6 Minimum wage earner -0,6 -0,9 -1,1 -1,2 Average wage earner government -0,6 -0,9 -1,1 -1,2 old age allowance -0,6 -0,9 -1,1 -1,2 numbers*1000 below poverty line 1 -0,9 -1,8 -2,6 -3,4 below poverty line 2 -0,9 -1,8 -2,6 -3,6 Secondly in the input sheet of Antiltax tax reductions and allowances are increased step by step until the sum of the decrease in income tax revenue and the increase of old age

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allowances in Antiltax equals the decrease of income tax that was implemented Curalyse6. Table Output Antiltax, variant including lower income tax Purchasing power abstract 2003 2004 2005 2006 in deviation of base line Average wage earner businesses 1,3 2,5 3,3 4,5 Minimum wage earner -0,6 -0,9 -1,1 -1,2 Average wage earner government 0,2 0,7 1,3 2,7 old age allowance 10,8 19,6 24,5 32,8 numbers*1000 below poverty line 1 -19,8 -20,7 -21,4 -22,2 below poverty line 2 -1,3 -2,5 -3,4 -22,5 base line figures: Discussion of the results: - The higher economic growth in combination with lower average income taxes

decreases the numbers below the poverty line after 4 years with 3400 (line1) or 3600 (line2) this is 13% of total below the poverty line in both cases. This is because the growth of employment and decrease of unemployment. These effect occur while in this scenario minimum wages and social security benefits in real terms go down because of the higher inflation.

- The same scenario, but now with the decrease of income tax rates geared to the lower income groups including persons with old age or unemployment allowance gives a much higher effect. Especially if thanks to the improvement of income in the lower income group, they almost all pass the poverty line (in 2003 concerning line 1 and in 2006 concerning line 2). In this scenario the real income growth of persons with only old age or unemployment allowances increases with 80%.

- However we see that the real income of the minimum wage earners is not influenced. That is because they do not profit from the decrease in taxes, because their income was already below the lowest tax bracket. However in case the real income of unemployed goes up, this will also affect the income of low wage groups. We also made calculations with Curalyse and Antiltax to calculate those effects (higher unemployment), but the discussion of that scenario is beyond the scope of this paper.

6 How to run this variant technically: • Give exports in Curalyse sheet SIM an impulse of 5% every year in 2003-2006 • Give an impulse in wage tax (row 151 Curalyse) of –21 (2003), -68 (2004), -119(2005), and -178

(2006). • Increase tax credits and old age allowance and unemployed allowance in 2003: 300 (in Input sheet

Antiltax cell T136), 900 in 2004, 1800 in 2005 and 3300 in 2006. These figures are found by iteration manually. (For example we changed the figure in sheet Input T136 till we found that the sum of the Tax decrease in sheet Sim2003 BM21 (from 15 to 0) plus the increase in allowances spending in Sim2003 BK27 (from 0 to 6, so sum 21), became equal to the impulse in tax decrease in Curalyse (also 21 mln. NAG). In later years these sums do not match the Curalyse impulse exactly but are approximations.

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4.b. Same variant, Kenya In this section we will try to repeat the variant we ran for the island of Curaçao for Kenya. Contrary to the Curalyse model for Curaçao the Macroabc model for Kenya (KTMM) is not publicly available. However, many different papers explaining KTMM are available on www.kippra.org. Therefore we are able to give an impression of the 5% export growth scenario using the demonstration model and some assumption about the macro-economic effects of this export boost. We used an updated demonstration version of MicromacroSim called MicromacroSimKenya-03-2003.xls for the calculation of this variant. This Excel-file is available as shareware on the MMC homepage, www.micromacroconsultants.com. In this version an increase in formal and informal employment leads to a decrease of the numbers in the traditional sector, leaving total labor force unchanged as compared to the reference path. We assume that an export boost of 5% per year for the period 2004-2007 will have the following macro-economic effects on the economy of Kenya. Year 2004 2005 2006 2007 Percentage change relative to initial situation Wage rate Businesses 0% 0% +1% +2% Wage rate Government 0% 0% +1% +2% Gross income informal sector 0% 0% +1% +2% Gross income traditional sector 0% 0% 0% 0% Employment Businesses +1% +1% +2% +2% Employment Government 0% 0% 0% 0% CPI 0% 0% 0% 0% Difference from initial situation in billions of Kenyan Shillings Change in government deficit +2 +7 +14 +22 These percentage figures are added to the initial values (the baseline) for 2004-2007 in the MicromacroSim program. Just like in the previous variant the extra gains for the government are used to lower the income taxes. However, in the MicromacroSim Kenya program the potential income tax revenues are calculated whereas the macro-economic assumption gives the actual revenue. The potential tax revenue appears to be three times as large as the actual tax revenue. Therefore the change in government deficit is implemented threefold in MicromacroSim. This implementation is done by lowering the tax rate in the first tax bracket until total wage-tax income is decreased by three times the amount in the table. The 10% tax rate in the first bracket was lowered to 8.93% in 2004, 6.49% in 2005, 3.39% in 2006, 0% in 2007 in the first bracket and 14.4% instead of 15% in the second bracket7.

7 Technical information:

• Add the macro-economic effects from the table to the base line in sheet Input of MicromacroSimKenya03-2003.xls in the green cells in the area I4-L13. For example, replace the 4 in cell K4 with a 5 (= 4 + the macroeconomic effect on the wage rate of businesses in 2006).

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The following table shows the output of MicromacroSim Kenya for this variant: In deviation of base line 2004 2005 2006 2007 CumulatedPurchasing power % changes Average wage earner enterprises 0,5 1,0 2,1 3,3 7,0Average wage earner government 0,6 1,3 2,5 3,8 8,1Worker in informal sector 1,1 2,5 4,1 5,3 12,9Worker in traditional sector 0,0 0,0 0,0 0,0 0,0Change of persons * 1000000 under poverty line 1 -0,061 -0,128 -0,266 -0,416 under poverty line 2 -0,077 -0,197 -0,422 -0,693 Discussion of the results: - The higher economic growth in combination with the lower income tax rate in the first bracket decreases the number below the poverty line after 4 years with 0,4 million (line 1) or 0,7 million (line 2) this is 4,5% and 6,4% of the total below the poverty lines respectively. - The lack of influence of this scenario on the income of the workers in the traditional income stems from the fact that the average income in this sector is too low to pay taxes and considerably lower than the lowest poverty line. Finally their income is assumed to grow with inflation, so there is no real income effect. Differences between the Curaçao and Kenya variant There are of course many factors that account for the different outcomes of the variants for Kenya and Curaçao. In the first place there are enormous differences between the economies of Curaçao and Kenya. Whereas Curaçao is a small island with 126000 inhabitants in which the largest part of export consists of tourism and the export/GDP ratio is around 70 %. Kenya on the other hand is an East-African country with 31 million inhabitants in which agricultural products constitute the largest part of exports and the export/GDP ratio is around 30 %. You will understand that under these circumstances an export boost will have a larger macro-economic impact on Curaçao when compared to Kenya. The MicromacroSim versions we used in these variants also differ from each other. The Kenya program we used is in fact a demonstration model in which many preliminary assumptions were made. Especially concerning the informal and the traditional sectors.

• Replace the 10% tax rate in the first bracket in row 55 with the percentages mentioned above

8,93% in 2004, 6,49% in 2005, 3,39% in 2006 and 0% in 2007. • Replace the 15% tax rate in the second bracket in cell L56 to 14,4% in 2007.

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5. Concluding Remarks The amount of people living below the poverty line is affected by three factors: macro economic developments, redistribution policies and other policies that directly affect the poor (micro credits, education etc.). In this paper we have presented a macro model and a poverty module that can be used in addition to a macro model to get a better idea of the consequences of macro economic and redistribution policies. Macro models can provide more information concerning poverty next to the growth of GDP, which is a very simple measure for poverty. Macroabc models also provide forecasts concerning wage rates and profits, consumer prices, employment (in businesses as well as civil servants) and unemployment or the amount of workers in the informal or traditional sector. We have demonstrated that in this paper for an export growth scenario in which the increase of government revenues is used to lower the tax burden for the lower income groups. Many other packages of policies can be simulated. The results will differ for different countries, but both the macro model and the micromacrosim module can be made for different countries. In the complementary poverty module Micromacrosim this additional information is combined with an income distribution of employed and unemployed or informal/ traditional sector, and a simulation of the gross-net tax regime. The output of this combination of macro model and poverty module consists of the effects of macro-economic developments and policy measures as well as redistribution policies on the purchasing power development of different income classes per socio-economic category, as well as effects on tax revenue and the amount of people living below the poverty line. The strength of this complementary poverty module is that it provides, for those countries that already have macro models in operation at the Ministry of Finance or at Economic Affairs, an easy to construct and easy to handle instrument that calculates how macro and redistribution policies affect the poor people in society. The weakness is that it does not provide the numbers below the poverty line in the income distribution of households, but only in the income distribution of individuals. Furthermore policies outside the field of macro-economics and income redistribution (for example micro credits etc.) are not included in the analysis. Our idea for further research is to find out how far and for what groups of policy variants, changes in the income distribution of individuals provide an indicator for the changes in the income distribution of households. This might be done by running some static simulations for countries that have a detailed micro database which produce output for the income distribution of households as well as individuals. That might result in an estimation of elasticities between developments for wage-earners and households. Another research idea is to improve the role of informal and traditional sector in macro models. This research might result in a new balance between the need to get more detailed information and the need to have a practical, as simple as possible, combination of macro and micro (poverty) models.

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18

Appendix : Sources and Literature Sources: • CBS, National Accounts figures and regular CBS publications • Quarterly and annual figures from homepage Central Bank as www.centralbank.go.ke

(Kenya) or www.centralbank.an (Curaçao). • CBS Household and Labour Force surveys Literature: Poland: • Department of Financial Policy and Analyses in the Ministry of Finance of Poland

and Micromacro Consultants, Reference Manual, Polish Macro'98 Model, Warsaw/The Hague, November 1997

Curaçao: • Department of Economic Affairs Curaçao and Micromacro Consultants, Reference

Manual Macro Model Curalyse, Curaçao/The Hague, October 1998 (Model in spreadsheet as shareware at www.micromacroconsultants.com )

• United Nations, New York, 2002, “Handbook of National Accounting”, Studies in methods Series F No. 81, New York 2002, Chapter VIID “Integration of accounting and modeling in the Caribbean: the ‘Antillyse’model and the National accounts of the Netherlands Antilles by Runy Calmera, Marein van Schaaijk and Jan van Tongeren.

Indonesia: • 14 Papers including Paper 14: Handbook MODFI, Macro Model Indonesia, Center

for Macro Economic Analysis of the Ministry of Finance/MMC, December 2002 (395 pages and CDROM with all Excel files, detailed study modules, and multi media slide shows with explanation. For internal use for the time being)

Kenya: • Karingi S. Njugana and Njugana S. Ndung'u: Macro Models of the Kenyan Economy:

A Review, KIPPRA paper December 1999 • ''Estimation Procedure and Estimated Results of the KIPPRA-Treasury Macro

Model'', KIPPRA, June 2001. • ‘’Theoretical Base for the Kenya Macro Model: The KIPPRA-Treasury Macro

Model, KIPPRA Discussion Paper 11, October 2001 • ‘’A Better Understanding of the Kenyan Economy: Simulations from the KIPPRA-

Treasury Macro Model” by Maureen Were and Stephen Karingi, Discussion Paper KIPPRA, No.. , August 2002

Suriname: • M. van Schaaijk, A Macro Model for a Small Economy, 1991, reprint 1993, The

Hague, Stuseco, ISBN 90-73732-03-4 • Imro San A Jong: Modelling the prospects for the future, in Pitou van Dijck (editor):

Suriname, the Economy, Ian Randle Publishers, Kingston 2001, 976-637-058-3 Other: • Micromacro Consultants, Macroabc NL, Euralyse, Micromacrosim poverty module

to Macroabc, www.micromacroconsultants.com • M. van Schaaijk and A. Verkade, Microtax International, CPB Working Paper No.51,

The Hague, April 1993

http://www.centralbank.go.ke/

http://www.centralbank.an/


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