Data requirements II: Building a country database for MAMS

Transcription

1 UNDP UN-DESA UN-ESCAP Data requirements II: Building a country database for MAMS Marco V. Sanchez (UN-DESA/DPAD) Presentation prepared for the inception and training workshop of the project Assessing Development Strategies to Achieve the MDGs in Asia and the Pacific, Bangkok, August,

2 Two key (Excel) files For core version: test-core.xls allows to solve MAMS without MDG module For MDG version test-mdg.xls enables calculation of MDG indicators and targets

3 General features Worksheet name usually provides data for set or parameter they represent Colouring scheme for worksheet tabs green: input is required yellow: input is optional red: not for inputs to solve MAMS without MDG module The required or suggested units are indicated. Percentages entered in decimal form (e.g., for 3%, type 0.03, not 3.)

4 Warning! The numbers in the two Excel files do not correspond to any country. They have been entered only to calibrate a trial version of MAMS. Country teams are highly recommended to work with country-specific data sets.

5 test-core.xls :: the basic database Large number of worksheets, most of which permit the user to define values for parameters used in MAMS. Time-related sets, a global set and SAM-related sets. Global set all accounts in the SAM each government capital stock (these are not included in the SAM unless value-added added is attributed to them) gender groups age categories (disaggregated by gender if needed) any additional items generated via aggregation mappings that cannot be inferred from the SAM between accounts for capital stocks and related investment accounts. between activities and investments (for gov).

6 test-core.xls :: main contents SAM provides the bulk of the data used to define base- year parameter values Miscellaneous data essentially easy to compile based on observed trends national accounts (including institutional block) and government accounts economy-wide growth (total and/or by sector) government consumption by commodity (growth) foreign borrowing and debt and related interest government borrowing and debt and related interest transfers between institutions annual growth rate for world price of exports annual growth rate for world price of imports growth rate for foreign direct investment base-year nominal exchange rate: LCU per US$

7 test-core.xls :: main contents Population and factor data also generally easy to compile, specially when household survey data are available population by household population in age cohort that: (i) enters grade 1 (ii) enters the labour force, often 15 years. population in labor force age (often 15-64) base-year employment by labour type and activity and also for the total labour force participation rates growth rates by factor to determine stock growth (may be difficult for non-labour factors) unemployment rates there are some labour-market related elasticities that may be more difficult to compile!

8 test-core.xls : main contents Government capital stocks need to be calculated historical government investment (in different capital stocks) data are used to estimate base-year capital stocks this information is complemented with data on depreciation and government consumption Data can even get more difficult to compile depreciation rates and net profit rates for private capital factors productivity growth (w.r.t growth in government capital stocks and the GDP trade share even by sector) and, the elasticity challenge (see next)

9 test-core.xls :: main contents Elasticities of substitution (for CES functions) by sector between imports and domestic output in domestic demand (sigmaq( sigmaq) between intermediates and factors among factors Elasticities of transformation by sector (for CET function) between exports and domestic supplies for domestic marketed output (sigmat( sigmat) Constant price elasticity of export demand by commodity (rhoe( rhoe) sigmaq sigmat rhoe c-agr c-nrexp c-ind c-ser 1.350

10 test-core.xls :: main contents Expenditure elasticity of market demand by commodity and household (to calibrate LES system) Elasticity of reservation wage for factor f with respect to: qhpc: : household per-capita consumption; pvaavg: : average value-added added price; erat: : employment rate (which equals one minus the unemployment rate); and cpi: : changes in the CPI. qhpc pva erat cpi f-labn f-labs f-labt

11 Elasticity values in MAMS Play a crucial role in the functioning of the model Affect the results of policy and external shock simulations. Basically two types Standard elasticities substitution, transformation, income-expenditure, expenditure, income-savings, and so on MDG-related elasticities (see separate presentation) determinants

12 Standard elasticities They are part of key functions in the model CES: constant elasticity of substitution CET: constant elasticity of transformation LES: linear expenditure system Entail optimization problems for producers and consumers CES production function: : (private) producer minimizes costs by finding the optimal quantity mix between intermediate consumption and production factors. Armington CES: : consumer faces the cost minimization problem of finding the optimal consumption mix between domestically produced goods/services and imported goods/services. CET: : producer maximizes profits by finding the optimal combined use of domestic output for domestic sales and exports.

13 Standard elasticities (cont.) CES and CET relative price shifts adjustment mechanism through which an optimal ratio for the mix of all the quantities involved in the producer and consumer problems is found, given the function constraints. in turn, the degree of response of quantity ratios to relative price shifts depends on the values of elasticities of substitution and transformation. Income elasticities of demand in the LES functions given a variation in household income, final demand shifts will depend on these elasticities How can all these elasticities be compiled?

14 Standard elasticities (cont.) Ideally they are already available in previous studies Annabi et al.. (2006, pp ) 34) provide a survey of values from econometric studies. Lluch,, Powell and Williams (1977, pp ) 55) provide values to calibrate the LES system. Likely many of them are not readily available, then what? Common practice: borrow elasticities that have been estimated for countries of similar development complemented with educated guesses after observing production and consumption structures and the flexibility of sectors relative to price shifts also, elasticities values are very often given equal values for different sectors/commodites commodites Although at times they are the last remaining resource to use, these practices do not increase the reliability of the parameters of the CGE model.

15 Standard elasticities (cont.) If data are available, it is better to estimate. Generally one needs time series for at least 25 years. Some other tips in what follows. For elasticities of substitution A demand equation system derived as a first order approximation of a CES function can be estimated: log ζ = a + b log p + ct + d1cri + d2ref ζ : the quantity ratio in the CES function p: relative price index that measures the ratio of the implicit price deflators of the quantities in ζ t: a time trend term [changing tastes over time to avoid misspecification] cri: dummy variable for crisis ref: dummy variables for structural-adjustment adjustment reform episodes

16 Standard elasticities (cont.) For elasticities of transformation In CET transformation function producers maximize per unit revenue from domestic and export sales. Then, the restricted form for the export supply can be set as: log(qec QEc/QXc) ) = a log δ0 0 + b log(pdc PDc/PEc) + cε t + d1 cri + d2 ref b: (expected to be negative) is the elasticity of transformation (though the elasticity has to be set with positive sign in the model) a: the intercept coefficient captures the effect of the other three terms in the CET function.

17 Standard elasticities (cont.) For income elasticities of demand Household survey data. A logarithmic commodity-wise expenditure demand function can be estimated using the OLS method: logcch = b0 0 + b1 logyh + ε Cch: total consumption of commodity c in household h b1: Engel elasticity Yh: total income of household type h excluding tax payments and savings

18 test-mdg.xls :: the MDG database Large number of worksheets, most of which permit the user to define values for parameters used in MAMS. MDG-related sets, particularly defined for education Mappings to aggregate MDG-related sectors supplied by the government and by the private sector Mappings to link education sector with labour types defined by education level f-labn f-labs f-labt c-edup c-edus c-edut YES YES YES

19 test-mdg.xls :: MDG key indicators mdg1: poverty rate mdg2: primary school completion rate mdg4: under-five mortality rate mdg5: maternal mortality rate (per 100 live births) mdg7a: access to save water mdg7b: access to basic sanitation

20 test-mdg.xls :: education data Number of enrolled by cycle in base year Number of non-cohort entrants to 1st grade in primary cycle in base year New students in each cycle in base year Data for student behaviour if 2005 is the base year and the primary education cycle comprises 6 years graduates from cycle enrolled continuing within cycle student share graduating from cycle among those who pass their current grade share of drop-outs outs and leavers in cycle c that enter the labor force

21 test-mdg.xls :: education data (cont.) Data for student behaviour ( ) 2005) share of labor-force force-age cohort outside school system that enter labor (type f) graduates from cycle enrolled continuing within cycle student share graduating from cycle among those who pass their current grade share of drop-outs outs and leavers in cycle c that enter the labor force share of labor-force force-age cohort outside school system that enter labor (type f)

22 test-mdg.xls :: education data (cont.) graduates from cycle enrolled continuing within cycle student share graduating from cycle among those who pass their current grade share of drop-outs outs and leavers in cycle c that enter the labor force share of labor-force force-age cohort outside school system that enter labor (type f) Data from household surveys and from the Ministry of Education are needed

23 test-mdg.xls :: education data (cont.) Most listed education data listed above are used to construct the behavioural shares an example for a 4-4 year primary education cycle and 2002 as the base year g1entry c-edup pass c-edup pass c-edup pass c-edus pass c-edut grdcont c-edup grdcont c-edus grdcont c-edut grdexit c-edup grdexit c-edus grdexit c-edut rep c-edup rep c-edup rep c-edus rep c-edut dropout c-edup dropout c-edup dropout c-edus dropout c-edut 0.112

24 test-mdg.xls :: worksheet mdgeduelas elasticity of indicator (1st two indices) with respect to determinant (3rd index) c-hlthg c-wtsn edu-qual f-capoinf hhdconspc mdg4 mdg7a mdg7b wage-prem mdg1 dummy mdg4 dummy mdg5 dummy mdg7a dummy mdg7b dummy g1entry c-edup pass c-edup pass c-edup pass c-edus pass c-edut grdcont c-edup grdcont c-edus grdcont c-edut

25 test-mdg.xls :: worksheet mdgeduscen values for determinants (under goal-achieving achieving scenario) and goals by MDG or education indicator c-hlthg c-wtsn edu-qual f-capoinf hhdconspc mdg4 mdg7a mdg7b wage-prem goal mdg4 dummy mdg5 dummy mdg7a dummy mdg7b dummy g1entry c-edup pass c-edup pass c-edup pass c-edus pass c-edut grdcont c-edup grdcont c-edus grdcont c-edut

26 test-mdg.xls :: worksheet ext_mdg0(mdg) ext_mdg0(mdg) extreme values for health MDGs mdg4 mdg

27 Key references Annabi, Nabil,, John Cockburn, and Bernard Decaluwé (2006). Functional Forms and Parametrization of CGE Models.. MPIA Working Paper Poverty and Economic Policy (PEP) Network (downloadable from net.org). Lluch,, Powell and Williams (1977). Patterns in Household Demand and Savings.. London: Oxford University Press. Sánchez,, Marco V. (2004) Rising Inequality and Falling Poverty in Costa Rica s s Agriculture during Trade Reform: A Macro-micro General Equilibrium Analysis. Maastricht: Shaker (see chapter 7 on model calibration).