Bangladesh: Poverty Reduction Strategy Paper

International Monetary Fund. Asia and Pacific Dept

doi:10.5089/9781475521344.002.A022

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Bangladesh: Poverty Reduction Strategy Paper

Author: International Monetary Fund. Asia and Pacific Dept

Publication Date:: 11 Mar 2013

ISBN:: 9781475521344

Language:: English

Keywords:: ISCR; CR; private sector; investment demand function; DCGE model; investment-saving identity; household demand; CES function; Agricultural commodities; Agricultural sector; Employment; Industrial sector; prices equation

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The Sixth Five Year Plan, as outlined in Bangladesh's Poverty Reduction Strategy Paper, targets strategic growth and employment. The medium-term macroeconomic framework plan entails the involvement of both the private and public sectors. Human resources development strategy programs reaching out to the poor and the vulnerable population, as well as environment, climate change, and disaster risk management, have been included in the plan. Managing regional disparities for shared growth and strategy for raising farm productivity and agricultural growth have been outlined. Diversifying exports and developing a dynamic manufacturing sector are all inclusive in the proposed plan.

Abstract

Results from the Dynamic CGE Model of Bangladesh

Introduction

The macro-economic framework for the SFYP has been used to generate consistent macro economic projections for the plan period. A dynamic computable general equilibrium (DCGE) model, based on an updated input-output table and a social accounting matrix (SAM) for Bangladesh for FY07, has been used to derive the sectoral implications of the macro projections considered in the SFYP. The key outcomes of the macroeconomic framework are linked to the DCGE model. Furthermore, an Employment Satellite Matrix (ESM), constructed for FY07 has been linked to the sectoral output growth derived from the DCGE model to generate the sectoral employment impacts.

The reason for employing a dynamic CGE model is due to fact that a dynamic CGE model is capable of capturing the growth effects of policy reforms. The inability of the static CGE model to account for growth effects make them inadequate for long-run analysis of the economic policies. They exclude accumulation effects and do not allow the study of transition path of an economy where short-run policy impacts are likely to be different from those of the long-run. To overcome this limitation we use a sequential dynamic CGE model. This kind of dynamics will not be the result of inter-temporal optimisation by economic agents. Instead, these agents have myopic behaviour. It is a series of static CGE models that are linked between periods by updating procedures for exogenous and endogenous variables. Capital stock is updated endogenously with a capital accumulation equation, whereas population (and total labour supply) is updated exogenously between periods. Also other variables such as public expenditure, transfers, technological change or debt accumulation are updated over time. The sequential dynamic CGE model has two major modules: static module and dynamic module. Descriptions of the static and dynamic modules of the model are presented in the subsequent sections.

Static Module of the DCGE Model

Production bloc

In each sector there is a representative firm, which earns capital income, pays dividends to households and pays direct income taxes to the government. We adopt a nested structure for production. Sectoral output is a Leontief function of value added and total intermediate consumption. Value added is in turn represented by a CES function of capital and composite labour. The latter is also represented by a CES function of two labour categories: skilled labour and unskilled labour. Both labour categories are assumed to be fully mobile in the model. In different production activities we assume that a representative firm remunerates factors of production and pays dividends to households.

The equations of the production bloc are provided below. The description of the variables and parameters is provided in the Annex.

\begin{matrix} (1) & {\begin{matrix} X S \end{matrix}}_{j} = M i n \end{matrix} [\frac{{C I}_{j}}{{i o}_{j}}, \frac{{V A}_{j}}{ν_{j}}]

\begin{matrix} (2) & {V A}_{j} = A_{j}^{K L} {[\propto_{i}^{K L} L D_{i}^{- ρ_{i}^{k l}} + (1 - \propto_{i}^{K L}) K D_{i}^{- ρ_{i}^{k l}}]}^{- 1 / ρ_{i}^{K L}} \end{matrix}

\begin{matrix} (3) & {L D}_{i} = A_{j}^{L L} {[\propto_{i}^{L L} {Q L}_{i}^{- ρ_{i}^{L L}} + (1 - \propto_{i}^{L L}) {N Q L}_{i}^{- ρ_{i}^{L L}}]}^{- 1 / ρ_{i}^{L L}} \end{matrix}

\begin{matrix} (4) & {\begin{matrix} C I \end{matrix}}_{j} = {i o}_{j} {X S}_{j} \end{matrix}

\begin{matrix} (5) & {\begin{matrix} D I \end{matrix}}_{i, j} = a i j_{i, j} C I_{j} \end{matrix}

\begin{matrix} (6) & {\begin{matrix} L D \end{matrix}}_{i} = {(\frac{α_{i}^{K L}}{1 - α_{i}^{K L}})}^{σ_{i}^{K L}} {(\frac{r_{i}}{w_{i}})}^{σ_{i}^{K L}} \end{matrix} {K D}_{i}

\begin{matrix} (7) & N Q L_{i} = {(\frac{α_{i}^{L L}}{1 - α_{i}^{L L}})}^{σ_{i}^{L L}} {(\frac{w q}{w n q})}^{α_{i}^{L L}} \end{matrix} Q L_{i}

Income and demand bloc

Households earn their income from production factors: skilled and unskilled labour, agricultural and non-agricultural capital. They also receive dividends, intra-household transfers, government transfers and remittances and pay direct income tax to the government. Household savings are a fixed proportion of total disposal income. Household demand is represented by a linear expenditure system (LES) derived from the maximisation of a Stone-Geary utility function. The model includes nine household categories according to characteristics of the household head, as identified in the HES household survey. Five of these categories correspond to rural households and four are of urban households. Minimal consumption levels are calibrated by using guess-estimates of the income elasticity and the Frisch parameters.

The government receives direct tax revenue from households and firms and indirect tax revenue on domestic and imported goods. Its expenditure is allocated between the consumption of goods and services (including public wages) and transfers. The model accounts for indirect or direct tax compensation in the case of a tariff cut. The equations are provided below:

\begin{matrix} (8) & {\begin{matrix} Y H \end{matrix}}_{h} = λ_{h}^{W Q} \cdot w q Σ_{j} {Q L}_{j} + λ_{h}^{W Q N} \cdot Σ_{j} {N Q L}_{j} + λ_{h}^{R} Σ_{n a g} r_{n a g} {K D}_{n a g} + λ_{h}^{L} \cdot Σ_{a g} r_{a g} {K D}_{a g} + \\ P_{i n d e x} {T G}_{h} + P_{i n d e x} {T H}_{h, h j} + P_{i n d e x} {T W H}_{h} + {D I V}_{h} \end{matrix}

\begin{matrix} (9) & {\begin{matrix} Y D H \end{matrix}}_{h} = {Y H}_{h} - {D T H}_{h} \end{matrix}

\begin{matrix} (10) & {\begin{matrix} S H \end{matrix}}_{h} = ν \cdot ψ_{h} \cdot {Y D H}_{h} \end{matrix}

\begin{matrix} (11) & Y F = λ^{R F} Σ_{i} r_{i} {K D}_{i} + λ^{L F} . r l . L A N D \end{matrix}

\begin{matrix} (12) & S F = Y F - Σ_{h} {D I V}_{h} - e . \end{matrix} {D I V}^{R O W} - D T F

\begin{matrix} (13) & Y G = Σ_{i} {T I}_{i} + Σ_{i} {T I E}_{i} + Σ_{i} {D T H}_{h} + D T F \end{matrix}

\begin{matrix} (14) & S G = Y G - G - P I N D E X Σ_{h} {T G}_{h} \end{matrix}

\begin{matrix} (15) & {\begin{matrix} T I \end{matrix}}_{i} = \end{matrix} t x_{i} (P_{i} X S_{i} - P E_{i} E X_{i}) + t x_{i} (1 + t m_{i}) . e . P W M_{i} M_{i}

\begin{matrix} (16) & {\begin{matrix} T I M \end{matrix}}_{i} = {t m}_{i} e . P W M_{i} M_{i} \end{matrix}

\begin{matrix} (17) & {\begin{matrix} T I E \end{matrix}}_{i} = {t e}_{i} {P E}_{i} {E X}_{i} \end{matrix}

\begin{matrix} (18) & {\begin{matrix} D T H \end{matrix}}_{h} = t y h_{h} {Y H}_{h} \end{matrix}

\begin{matrix} (19) & D T H = t y f . Y F \end{matrix}

\begin{matrix} (20) & {\begin{matrix} C T H \end{matrix}}_{h} = {Y D H}_{h} - {S H}_{h} \end{matrix}

\begin{matrix} (21) & {\begin{matrix} P C \end{matrix}}_{I} C_{i, h} = {P C}_{i} C_{i, h}^{m i n} + γ_{i, h} ({C T H}_{h} - Σ_{j} {P C}_{j} C_{j, h}^{m i n}) \end{matrix}

\begin{matrix} (22) & G = {C G}_{s e r} {P C}_{s e r} \end{matrix}

\begin{matrix} (23) & {\begin{matrix} I N V \end{matrix}}_{i} = \frac{μ_{i} I T}{{P C}_{i}} \end{matrix}

\begin{matrix} (24) & D I T_{i} = Σ_{j} D I_{j} \end{matrix}

International Trade

We assume that foreign and domestic goods are imperfect substitutes. This geographical differentiation is introduced by the standard Armington assumption with a constant elasticity of substitution function (CES) between imports and domestic goods. On the supply side, producers make an optimal distribution of their production between exports and local sales according to a constant elasticity of transformation (CET) function. Furthermore, we assume a finitely elastic export demand function that expresses the limited power of the local producers on the world market. In order to increase their exports, local producers may decrease their free on board (FOB) prices. The equations are provided below:

\begin{matrix} (25) & {\begin{matrix} X S \end{matrix}}_{i} = B_{i}^{E} {[β_{i}^{E} E X_{i}^{k_{i}^{E}} + (1 + β_{i}^{E}) D_{i}^{k_{i}^{E}}]}^{\frac{1}{k_{i}^{B}}} \end{matrix}

\begin{matrix} (26) & {\begin{matrix} E X \end{matrix}}_{i} = {[(\frac{{P E}_{i}}{{P L}_{i}}) (\frac{1 - β_{i}^{E}}{β_{i}^{E}})]}^{τ_{i}^{E}} D_{i} \end{matrix}

\begin{matrix} (27) & {\begin{matrix} E X D \end{matrix}}_{i} = E X D_{i}^{o} . {(\frac{{P W E}_{i}}{{{P E}_{-} F O B}_{i}})}^{{e l a s t}_{i}} \end{matrix}

\begin{matrix} (28) & Q_{i} = A_{i}^{M} {[α_{i}^{M} M_{i}^{- ρ_{i}^{M}} + (1 - α_{i}^{M}) D_{i}^{- ρ_{i}^{M}}]}^{\frac{- 1}{ρ_{i}^{M}}} \end{matrix}

\begin{matrix} (29) & M_{i} = \end{matrix} {[(\frac{{P D}_{i}}{{P M}_{i}}) (\frac{α_{i}^{M}}{1 - α_{i}^{M}})]}^{σ_{i}^{M}} D_{i}

\begin{matrix} (30) & C A B = Σ_{i} P W M_{i} M_{i} + λ^{R O W} Σ_{i} r_{i} K D_{i} / e \end{matrix} + D I V^{R O W} - Σ_{i} P E_{F O B_{i}} E X_{i}

Price blocs

The prices equations are provided below. The nominal exchange rate is the numéraire in each period.

\begin{matrix} (31) & (25) {P V}_{j} \end{matrix} = \frac{P_{j} {X S}_{j} - Σ_{i} {P C}_{i} {D I}_{i, j}}{{V A}_{j}}

\begin{matrix} (32) & r_{i} = \frac{{P V}_{i} {V A}_{i} - w_{i} {L D}_{i}}{{K D}_{i}} \end{matrix}

\begin{matrix} (33) & w_{i} = \frac{w q . {Q L}_{i} - w n q . {N Q L}_{i}}{{L D}_{i}} \end{matrix}

\begin{matrix} (34) & {\begin{matrix} P D \end{matrix}}_{i} = (1 + {t x}_{i}) {P L}_{i} \end{matrix}

\begin{matrix} (35) & {\begin{matrix} P M \end{matrix}}_{i} = (1 + {t x}_{i}) . (1 + {t m}_{i}) . e . P W M_{i} \end{matrix}

\begin{matrix} (36) & {\begin{matrix} P E \end{matrix}}_{i} = \frac{e . {P E}_{-} {F O B}_{i}}{1 + {t e}_{i}} \end{matrix}

\begin{matrix} (37) & {\begin{matrix} P C \end{matrix}}_{i} Q_{i} = {P D}_{i} D_{i} + P M_{i} M_{i} \end{matrix}

\begin{matrix} (38) & P_{i} {X S}_{i} = {P L}_{i} D_{i} + {P E}_{i} {E X}_{i} \end{matrix}

\begin{matrix} (39) & P_{i n v} \end{matrix} = Π_{i} {(\frac{{P C}_{i}}{μ_{i}})}^{μ_{i}}

\begin{matrix} (40) & P_{i n d e x} \end{matrix} = Σ_{i} δ_{i} {P V}_{i}

Equilibrium Condition

General equilibrium is defined by the equality (in each period) between supply and demand of goods and factors and the investment-saving identity. The equations are provided below:

\begin{matrix} (41) & Q_{i} = {D I T}_{i} + Σ_{h} C_{i, h} + {I N V}_{i} \end{matrix} + {D s t k}_{i}

\begin{matrix} (42) & {\begin{matrix} E X \end{matrix}}_{i} = {E X D}_{i} \end{matrix}

\begin{matrix} (43) & L S Q = Σ_{j} Q L_{j} \end{matrix}

\begin{matrix} (44) & L S N Q = Σ_{j} {N Q L}_{j} \end{matrix}

\begin{matrix} (45) & I T + Σ_{i} P C_{i} D s t k_{i} \end{matrix} = Σ_{h} S H_{h} + S F + S G + e . C A B

Dynamic Module of the DCGE Model

In every period capital stock is updated with a capital accumulation equation. We assume that the stocks are measured at the beginning of the period and that their flows are measured at the end of the period. We use an investment demand function to determine how new investments will be distributed between the different sectors. This can also be done through a capital distribution function¹⁵. Investment here is not by origin (product) but rather by sector of destination. The investment demand function used here is similar to those proposed by Bourguignon et al. (1989), and Jung and Thorbecke (2003). The capital accumulation rate (ratio of investment to capital stock) is increasing with respect to the ratio of the rate of return to capital and its user cost. The latter is equal to the dual price of investment times the sum of the depreciation rate and the exogenous real interest rate. The elasticity of the accumulation rate with respect to the ratio of return to capital and its user cost is assumed to be equal to two. By introducing investment by destination, we respect the equality condition with total investment by origin in the SAM (Social Accounting Matrix). Besides this, investment by destination is used to calibrate the sectoral capital stock in base run.

Total labour supply is an endogenous variable, although it is assumed to simply increase at the exogenous population growth rate. Note that the minimal level of consumption in the LES function also increases (as do other nominal variables, like transfers) at the same rate. The exogenous dynamic updating of the model includes nominal variables (that are indexed), government savings and the current account balance. The equilibrium between total savings and total investment is reached by means of an adjustment variable introduced in the investment demand function. Moreover, the government budget equilibrium is met by a neutral tax adjustment.

The model is formulated as a static model that is solved sequentially over a certain period time horizon.¹⁶ The model is homogenous in prices and calibrated in a way to generate “steady state” paths. In the baseline all the variables are increasing, in level, at the same rate and the prices remain constant. The homogeneity test (for example, a shock on the numéraire – the nominal exchange rate – with the “steady state” characteristics) generates the same shock on prices, and unchanged real values, along the counterfactual path. This method is used to facilitate welfare and poverty analysis since all prices remain constant along the business as usual (BaU) path.

It is, however, important to note that, in contrast to the static CGE models, which make counterfactual analysis with respect to the base run (generally the initial SAM), a dynamic CGE model allows the economy to grow even in the absence of a shock. This scenario of the economy (without a shock) is termed as the business-as-usual (BAU) scenario. The counterfactual analysis of any simulation under the dynamic CGE model is, therefore, done with respect to this growth path. One of the salient features of the dynamic model is that it takes into account not only efficiency effects, as also present in the static models, but also accumulation effects. The sectoral accumulation effects are linked to the ratio between the rate of return to the capital stock and the cost of investment goods. The equations of the dynamic bloc are provided below.

\begin{matrix} (46) & {\begin{matrix} K D \end{matrix}}_{i, t + 1} = (1 - δ) {K D}_{i, t} + {I n d}_{i, t} \end{matrix}

\begin{matrix} (47) & {\begin{matrix} L S Q \end{matrix}}_{t + 1} = (1 + n g) . {L S Q}_{t} \end{matrix}

\begin{matrix} (48) & {\begin{matrix} L S N Q \end{matrix}}_{q} = (1 + n g) . {N Q L}_{t} \end{matrix}

\begin{matrix} (49) & C_{i, h, t + 1}^{m i n} = (1 + n g) C_{i, h, t}^{m i n} \end{matrix}

\begin{matrix} (50) & \frac{{I n d}_{i, t}}{{K D}_{i, t}} = A_{i}^{I K} {(\frac{R_{i, t}}{U_{i, t}})}^{2} \end{matrix}

\begin{matrix} (51) & U_{i, t} = {P i n v}_{t} (i r + δ_{i}) \end{matrix}

\begin{matrix} (52) & {\begin{matrix} I T \end{matrix}}_{t} = {p i n v}_{t} . Σ_{i} {I n d}_{i, t} \end{matrix}

\begin{matrix} (53) & {\begin{matrix} S G \end{matrix}}_{t + 1} = (1 + n g) {S G}_{t} \end{matrix}

\begin{matrix} (54) & {\begin{matrix} C A B \end{matrix}}_{t + 1} = (1 + n g) {C A B}_{t} \end{matrix}

\begin{matrix} (55) & {\begin{matrix} T G \end{matrix}}_{t + 1} = (1 + n g) {T G}_{i} \end{matrix}

\begin{matrix} (56) & {C G}_{t + 1} = (1 + n g) {C G}_{t} \end{matrix}

\begin{matrix} (57) & {\begin{matrix} D s t k \end{matrix}}_{t + 1} = (1 + n g) D s t k_{t} \end{matrix}

\begin{matrix} (58) & {\begin{matrix} D I V \end{matrix}}_{t + 1} = (1 + n g) {D I V}_{t} \end{matrix}

\begin{matrix} (59) & {\begin{matrix} {\begin{matrix} D I V \end{matrix}}_{-} R O W \end{matrix}}_{t + 1} = (1 + n g) {D I V}_{-} {R O W}_{t} \end{matrix}

\begin{matrix} (60) & {\begin{matrix} T W H \end{matrix}}_{t + 1} = (1 + n g) {T W H}_{t} \end{matrix}

\begin{matrix} (61) & {\begin{matrix} T H \end{matrix}}_{h, h j, t + 1} = (1 + n g) {T H}_{h, h j, t} \end{matrix}

\begin{matrix} (62) & E X D_{t + 1}^{o} = (1 + n g) {E X D}_{t}^{o} \end{matrix}

The Bangladesh Social Accounting Matrix for 2006-07

For the purpose this exercise, a SAM for 2006/07 for Bangladesh has been constructed. SAM 2006/07 composed of 189 accounts. The distributions of 189 accounts are: (i) 86 activities; (ii) 86 commodities; (iii) 4 factors of production; (iv) 11 current institutions; and (v) 2 capital institutions. Data on various components of the demand side have been collected from Bangladesh Bureau of Statistics (BBS). In particular, data on public consumption by 86 commodities, gross fixed capital formation by 86 commodities, and private consumption by 86 commodities have been obtained from BBS. The vector of private consumption data is further distributed among the eight representative household groups using the unit record data of Household Income and Expenditure Survey (HIES) of 2005. Data on exports of goods and services are collected from the Export Promotion Bureau and Bangladesh Bank (i.e. the central bank of Bangladesh). Supply side composed of value added and imports of goods and services. We used disaggregated BBS data to derive the value added vector for the 86 activities. Data on imports of goods and services are collected from the Bangladesh Bank and the National Board of Revenue. Information on direct and indirect taxes and subsidies has been collected from the National Board of Revenue and the Finance division, Ministry of Finance. Input-output flow matrix for 2006/07 has been derived by using newly conducted surveys for few selected activities and updating the previous technology vectors using secondary information. More specifically, out of the 86 activities, technology vectors of five important activities such as paddy, livestock, poultry, pharmaceuticals and information technology (ICT) have been derived using the field survey data. The technology vectors of the remaining activities are updated using secondary information.

For the DCGE model, we use an aggregated version of the SAM of Bangladesh that includes 15 sectors, four factors of production: skilled and unskilled labour, agricultural and non-agricultural capital. An important feature of the SAM is the decomposition of the households into seven groups. Households are classified in terms of location - urban and rural. In case of rural households, occupation and ownership of agricultural capital by the household is the main criterion to differentiate household groups. Initially making a preliminary distinction between agricultural and non-agricultural occupation groups, the agricultural group is then classified into four classes according to ownership of agricultural capital. Thereby there are five groups: Landless (No cultivable land); marginal farmers (up to 0.49 acre of land); small farmers (0.5 to 2.49 acres of land); large farmers (2.50 acres of land and above); Non-Agricultural. Urban households are classified into two categories according to the educational level of the household head. These are: Low Education (below class X) and High Education (above class X). Table 1 provides the features of the 2006-07 SAM of Bangladesh.

Table 1:

Features of 2006-07 SAM of Bangladesh

Results of the DCGE Model and the Projections

Sectoral Growth Rates

The growth rates for 14 sectors of the DCGE model for the period between 2009-10 and 20014-15 are reported in Table 2. It appears that the cereal crop sector will experience a growth rate of around 4.7 percent during the plan period, whereas the commercial crops sector will experience higher growth rate than that of crop agriculture suggesting a shift in the production pattern in the agricultural sector. By 2014-15, the growth rate of the overall agricultural sector will be 4.3 percent. The overall industrial sector will experience a rise in growth rate by almost 100 percent at the end of plan period from its current growth rate. Growth in the textile and clothing sector, machinery sector and other industries will be the major drivers of the industrial growth rate. The construction and services sectors will also experience steady rise in growth rates.

Table 2:

Sectoral Growth Rates

Source: DCGE Model

Table 2:

Sectoral Growth Rates

	2009-10 (actual)	2010-11 (est)	2011-12	2012-13	2013-14	2014-15
Agriculture	5.3	4.9	4.5	4.4	4.3	4.3
Cereal Crops	5.8	5.4	5.0	4.8	4.7	4.7
Commercial Crops	6.5	6.0	5.5	5.4	5.3	5.3
Livestock-Poultry-fishing	4.0	3.7	3.4	3.3	3.2	3.2
Forestry	5.2	4.8	4.4	4.3	4.2	4.2
Other Agriculture	2.1	1.9	1.7	1.7	1.7	1.7
Industry	6.6	9.2	9.6	9.9	10.5	11.5
of which Manufacturing	6.5	9.5	9.8	10.1	10.7	11.7
Other Food	6.1	7.2	8.4	8.7	10.5	12.5
Leather Products	7.7	8.5	9.4	10.5	11.2	12.2
Textile and Clothing	7.6	14.4	13.5	13.8	14.2	15.1
Chemical-Fertilizer	5.3	6.1	6.7	6.8	7.0	7.4
Machinery	5.9	6.2	6.6	6.7	7.2	7.9
Petroleum Products	4.3	4.7	5.5	5.6	5.9	6.1
Other industries	8.2	8.4	8.9	9.1	9.2	9.3
Construction	6.0	6.4	6.6	6.8	7.8	8.1
Services	6.5	6.6	6.8	7.1	7.3	7.8
GDP GROWTH	6.2	6.7	6.9	7.2	7.6	8.0

Source: DCGE Model

Table 2:

Sectoral Growth Rates

	2009-10 (actual)	2010-11 (est)	2011-12	2012-13	2013-14	2014-15
Agriculture	5.3	4.9	4.5	4.4	4.3	4.3
Cereal Crops	5.8	5.4	5.0	4.8	4.7	4.7
Commercial Crops	6.5	6.0	5.5	5.4	5.3	5.3
Livestock-Poultry-fishing	4.0	3.7	3.4	3.3	3.2	3.2
Forestry	5.2	4.8	4.4	4.3	4.2	4.2
Other Agriculture	2.1	1.9	1.7	1.7	1.7	1.7
Industry	6.6	9.2	9.6	9.9	10.5	11.5
of which Manufacturing	6.5	9.5	9.8	10.1	10.7	11.7
Other Food	6.1	7.2	8.4	8.7	10.5	12.5
Leather Products	7.7	8.5	9.4	10.5	11.2	12.2
Textile and Clothing	7.6	14.4	13.5	13.8	14.2	15.1
Chemical-Fertilizer	5.3	6.1	6.7	6.8	7.0	7.4
Machinery	5.9	6.2	6.6	6.7	7.2	7.9
Petroleum Products	4.3	4.7	5.5	5.6	5.9	6.1
Other industries	8.2	8.4	8.9	9.1	9.2	9.3
Construction	6.0	6.4	6.6	6.8	7.8	8.1
Services	6.5	6.6	6.8	7.1	7.3	7.8
GDP GROWTH	6.2	6.7	6.9	7.2	7.6	8.0

Source: DCGE Model

Sectoral Shares in GDP

Differential growth rates for different sectors, as reported in Table 2, lead to varying sectoral shares in GDP over the plan period. The agricultural sector, as a whole, will experience decline in the share in GDP from 18.6 percent in 2009-10 to 15.5 percent in 2014-15. All the agricultural sub-sectors will experience decline in their respective shares. The major fall will be in the case of cereal crops.

In the case of industrial sector, the overall share will rise from 19.1 percent in 2009-10 to 22.3 percent in 2014-15. All industrial sub-sectors, except chemical-fertiliser, will experience rise in their shares in GDP. The most notable rise will be in the cases of textile and clothing and machinery sectors.

The share of construction sector in GDP will rise by 0.3 percentage points by the end of the plan period from its current share. The share of services sector will fall by 0.4 percentage points by the end of the plan period.

Sectoral Employment

As mentioned before, the sectoral output changes from the DCGE model are linked to the employment satellite matrix to derive the sectoral employment effects of the sectoral growth. Table 4 presents the projections of the total number of labour force to be employed by different sectors during the plan period. The number of labour force employed in the agricultural sector will rise from 25628150 in 2009-10 to 31159781 in 2014-15. All agricultural sub-sectors will experience rise in employment. However, the most significant rise in employment will be observed in the industrial sector where employment will rise from 6792516 2009-10 to 11073693 in 2014-15. Sub-sectors like textile and clothing and other industries will generate major incremental employment in the industrial sector. Finally, the constriction and services sectors will also generate substantial additional employment during the plan period. The growth rate in employment will rise from its current level of 5.04 percent to 7.19 percent by the end of the plan period. The annual average additional employment will be 4124001.

Table 3:

Sectoral Shares in GDP

Source: DCGE Model

Table 3:

Sectoral Shares in GDP

	2009-10 (actual)	2010-11 (est)	2011-12	2012-13	2013-14	2014-15
Agriculture	18.6	18.4	17.7	16.9	16.2	15.5
Cereal Crops	6.4	6.3	6.0	5.7	5.4	5.1
Commercial Crops	4.8	4.7	4.5	4.4	4.3	4.2
Livestock-Poultry-fishing	3.3	3.3	3.2	3.0	2.9	2.8
Forestry	1.4	1.4	1.4	1.3	1.2	1.1
Other Agriculture	2.7	2.7	2.6	2.5	2.4	2.3
Industry	19.1	19.4	19.9	20.8	21.6	22.3
of which Manufacturing	17.9	18.2	18.7	19.6	20.4	21.1
Other Food	2.5	2.5	2.6	2.7	2.8	2.9
Leather Products	0.9	0.9	0.9	1.0	1.1	1.1
Textile and Clothing	6.6	6.8	7.0	7.4	7.8	8.2
Chemical-Fertilizer	2.0	2.0	2.1	2.2	2.3	2.4
Machinery	5.1	5.2	5.3	5.4	5.5	5.6
Petroleum Products	0.8	0.8	0.8	0.9	0.9	0.9
Other industries	1.2	1.2	1.2	1.2	1.2	1.2
Construction	8.3	8.2	8.4	8.5	8.6	8.6
Services	54.0	54.0	54.0	53.8	53.6	53.6
	100.0	100.0	100.0	100.0	100.0	100.0

Source: DCGE Model

Table 3:

Sectoral Shares in GDP

	2009-10 (actual)	2010-11 (est)	2011-12	2012-13	2013-14	2014-15
Agriculture	18.6	18.4	17.7	16.9	16.2	15.5
Cereal Crops	6.4	6.3	6.0	5.7	5.4	5.1
Commercial Crops	4.8	4.7	4.5	4.4	4.3	4.2
Livestock-Poultry-fishing	3.3	3.3	3.2	3.0	2.9	2.8
Forestry	1.4	1.4	1.4	1.3	1.2	1.1
Other Agriculture	2.7	2.7	2.6	2.5	2.4	2.3
Industry	19.1	19.4	19.9	20.8	21.6	22.3
of which Manufacturing	17.9	18.2	18.7	19.6	20.4	21.1
Other Food	2.5	2.5	2.6	2.7	2.8	2.9
Leather Products	0.9	0.9	0.9	1.0	1.1	1.1
Textile and Clothing	6.6	6.8	7.0	7.4	7.8	8.2
Chemical-Fertilizer	2.0	2.0	2.1	2.2	2.3	2.4
Machinery	5.1	5.2	5.3	5.4	5.5	5.6
Petroleum Products	0.8	0.8	0.8	0.9	0.9	0.9
Other industries	1.2	1.2	1.2	1.2	1.2	1.2
Construction	8.3	8.2	8.4	8.5	8.6	8.6
Services	54.0	54.0	54.0	53.8	53.6	53.6
	100.0	100.0	100.0	100.0	100.0	100.0

Source: DCGE Model

Table 4:

Sectoral Employment (Number of labour force employed)

Source: DCGE Model and Employment Satellite Matrix

Table 4:

Sectoral Employment (Number of labour force employed)

	2009-10	2010-11	2011-12	2012-13	2013-14	2014-15
Agriculture	25628150	26550256	27544257	28621862	29824054	31159781
Cereal Crops	14923825	15440189	15996036	16597487	17268026	18012278
Commercial Crops	3709788	3848905	3999397	4162973	4345727	4549107
Livestock-Poultry-fishing	6096230	6323619	6568976	6835676	7133712	7465429
Forestry	595461	624460	656120	690894	730206	774530
Other Agriculture	302846	313083	323727	334831	346383	358437
Industry	6792516	7413955	8122573	8948828	9916576	11073693
Other Food	345576	371840	401290	434517	473145	517999
Leather Products	116173	123584	131790	140937	151436	163476
Textile and clothing	3022149	3350333	3729957	4171976	4703805	5344395
Chemical-Fertilizer	172938	185926	200484	216863	235904	257985
Machinery	52050	55225	58732	62632	67098	72197
Petroleum Products	12510	13308	14191	15176	16307	17603
Other Industries	3071120	3313738	3586128	3906728	4268881	4700038
Construction	1991126	2135284	2298206	2477466	2672691	2895860
Services	23212784	24761077	26469591	28370107	30582976	33115246
Total Employment	57624577	60860572	64434627	68418263	72996296	78244580
Employment Growth Rate	5.04	5.62	5.87	6.18	6.69	7.19
Additional Employment	2765274	3235995	3574055	3983637	4578033	5248284

Source: DCGE Model and Employment Satellite Matrix

Table 4:

Sectoral Employment (Number of labour force employed)

	2009-10	2010-11	2011-12	2012-13	2013-14	2014-15
Agriculture	25628150	26550256	27544257	28621862	29824054	31159781
Cereal Crops	14923825	15440189	15996036	16597487	17268026	18012278
Commercial Crops	3709788	3848905	3999397	4162973	4345727	4549107
Livestock-Poultry-fishing	6096230	6323619	6568976	6835676	7133712	7465429
Forestry	595461	624460	656120	690894	730206	774530
Other Agriculture	302846	313083	323727	334831	346383	358437
Industry	6792516	7413955	8122573	8948828	9916576	11073693
Other Food	345576	371840	401290	434517	473145	517999
Leather Products	116173	123584	131790	140937	151436	163476
Textile and clothing	3022149	3350333	3729957	4171976	4703805	5344395
Chemical-Fertilizer	172938	185926	200484	216863	235904	257985
Machinery	52050	55225	58732	62632	67098	72197
Petroleum Products	12510	13308	14191	15176	16307	17603
Other Industries	3071120	3313738	3586128	3906728	4268881	4700038
Construction	1991126	2135284	2298206	2477466	2672691	2895860
Services	23212784	24761077	26469591	28370107	30582976	33115246
Total Employment	57624577	60860572	64434627	68418263	72996296	78244580
Employment Growth Rate	5.04	5.62	5.87	6.18	6.69	7.19
Additional Employment	2765274	3235995	3574055	3983637	4578033	5248284

Source: DCGE Model and Employment Satellite Matrix

Table 5 indicates that during the plan period the agricultural sector as a whole will encounter fall in the share of employment from its current 44.5 percent to 39.8 percent at the end of plan period. Three major agricultural sub-sectors, i.e. cereal crops, commercial crops and livestockpoultry-fishing will experience fall in the shares by notable margins.

Table 5:

Sectoral Employment Share

Source: DCGE Model and Employment Satellite Matrix

Table 5:

Sectoral Employment Share

	2009-10	2010-11	2011-12	2012-13	2013-14	2014-15
Agriculture	44.5	43.6	42.7	41.8	40.9	39.8
Cereal Crops	25.9	25.4	24.8	24.3	23.7	23.0
Commercial Crops	6.4	6.3	6.2	6.1	6.0	5.8
Livestock-Poultry-fishing	10.6	10.4	10.2	10.0	9.8	9.5
Forestry	1.0	1.0	1.0	1.0	1.0	1.0
Other Agriculture	0.5	0.5	0.5	0.5	0.5	0.5
Industry	11.8	12.2	12.6	13.1	13.6	14.2
Other Food	0.6	0.6	0.6	0.6	0.6	0.7
Leather Products	0.2	0.2	0.2	0.2	0.2	0.2
Textile and Clothing	5.2	5.5	5.7	6.1	6.4	6.8
Chemical-Fertilizer	0.3	0.3	0.3	0.3	0.3	0.3
Machinery	0.1	0.1	0.1	0.1	0.1	0.1
Petroleum Products	0.0	0.0	0.0	0.0	0.0	0.0
Other Industries	5.3	5.4	5.6	5.7	5.8	6.0
Construction	3.5	3.5	3.6	3.6	3.7	3.7
Services	40.4	40.8	41.2	41.5	41.9	42.4
Total Employment	100.0	100.0	100.0	100.0	100.0	100.0

Source: DCGE Model and Employment Satellite Matrix

Table 5:

Sectoral Employment Share

	2009-10	2010-11	2011-12	2012-13	2013-14	2014-15
Agriculture	44.5	43.6	42.7	41.8	40.9	39.8
Cereal Crops	25.9	25.4	24.8	24.3	23.7	23.0
Commercial Crops	6.4	6.3	6.2	6.1	6.0	5.8
Livestock-Poultry-fishing	10.6	10.4	10.2	10.0	9.8	9.5
Forestry	1.0	1.0	1.0	1.0	1.0	1.0
Other Agriculture	0.5	0.5	0.5	0.5	0.5	0.5
Industry	11.8	12.2	12.6	13.1	13.6	14.2
Other Food	0.6	0.6	0.6	0.6	0.6	0.7
Leather Products	0.2	0.2	0.2	0.2	0.2	0.2
Textile and Clothing	5.2	5.5	5.7	6.1	6.4	6.8
Chemical-Fertilizer	0.3	0.3	0.3	0.3	0.3	0.3
Machinery	0.1	0.1	0.1	0.1	0.1	0.1
Petroleum Products	0.0	0.0	0.0	0.0	0.0	0.0
Other Industries	5.3	5.4	5.6	5.7	5.8	6.0
Construction	3.5	3.5	3.6	3.6	3.7	3.7
Services	40.4	40.8	41.2	41.5	41.9	42.4
Total Employment	100.0	100.0	100.0	100.0	100.0	100.0

Source: DCGE Model and Employment Satellite Matrix

In the case of industry, the sector as a whole will experience a rise in the share of total employment from 11.8 percent in 2009-10 to 14.2 percent in 2014-15. The notable rises in the shares of employment are observed in sub-sectors like textile and clothing and other industries. The construction sector will go through some marginal rise in the share whereas the services sector will experience rise in the share by 2 percentage points during the plan period.

Annex Description of the Variables and Parameters of the Dynamic CGE Model

Endogenous variables

Exogenous variables

Parameters

Production functions

CES function between capital and labor

CES function between skilled and unskilled labor

CES function between imports and domestic production

CET function between domestic production and exports

LES consumption function

Tax rates

Other parameters

Reference

Abbink, G. A., M. C. Braber, and S. I. Cohen. 1995. “A SAM-CGE Demonstration Model for Indonesia: A Static and Dynamic Specifications and Experiments.” International Economic Journal 9 (3): 15–33.
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Bourguignon, F., W. H. Branson, and J. de Melo. 1989. “Macroeconomic Adjustment and Income Distribution: A Macro-Micro Simulation Model.” OECD Technical Paper 1. Paris.
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- Export Citation
Jung, H. S., and E. Thorbecke. 2003. “The Impact of Public Education Expenditure on Human Capital, Growth, and Poverty in Tanzania and Zambia: A General Equilibrium Approach.” Journal of Policy Modeling 25: 701–25.
- Search Google Scholar
- Export Citation

Abbink et al (1995) use a sequential dynamic CGE model for Indonesia where total investment is distributed as a function of base year sectoral shares in total capital remuneration and sectoral profit rates.

The model is formulated as a system of non linear equations solved simultaneously as a constrained non-linear system (CNS) with GAMS/Conopt3 solver.

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Bangladesh: Poverty Reduction Strategy Paper

Author: International Monetary Fund. Asia and Pacific Dept

Volume/Issue:: Volume 2013: Issue 063

Publisher:: International Monetary Fund

ISBN:: 9781475521344

ISSN:: 1934-7685

Pages:: 916

DOI:: https://doi.org/10.5089/9781475521344.002

Set	Description of Elements
Activities
Agriculture (5)	Cereal Crops, Commercial Crops, Livestock-Poultry-fishing, Forestry, Other Agriculture
Industries (7)	Other Food, Leather Products, Textile, Chemical-Fertilizer, Machinery, Petroleum Products, Other Industries
Services (2)	Construction, Services.
Institutions
Households (7)	− Rural Agriculture: 4 categories according to land ownership: Landless, Marginal Farmer, Small Farmer, and Large Farmer. - Rural Non-Farmer: 1 category according to occupation - Urban: 2 categories according to the level of education of the household’s head: Low Education and High Education.
Others (2)	Government, Rest of the World
Factors of production
Labour (4)	Unskilled Male: Class 0-IX Unskilled Female: Class 0-IX Skilled Male: Class X and above Skilled Female: Class X and above
Capital (2)	Agricultural capital Non agricultural capital

Set	Description of Elements
Activities
Agriculture (5)	Cereal Crops, Commercial Crops, Livestock-Poultry-fishing, Forestry, Other Agriculture
Industries (7)	Other Food, Leather Products, Textile, Chemical-Fertilizer, Machinery, Petroleum Products, Other Industries
Services (2)	Construction, Services.
Institutions
Households (7)	− Rural Agriculture: 4 categories according to land ownership: Landless, Marginal Farmer, Small Farmer, and Large Farmer. - Rural Non-Farmer: 1 category according to occupation - Urban: 2 categories according to the level of education of the household’s head: Low Education and High Education.
Others (2)	Government, Rest of the World
Factors of production
Labour (4)	Unskilled Male: Class 0-IX Unskilled Female: Class 0-IX Skilled Male: Class X and above Skilled Female: Class X and above
Capital (2)	Agricultural capital Non agricultural capital

C_i,h :	Household h’s consumption of good i (volume)
CF :	Composite agricultural capital-labor factor (volume)
CI_j :	Total intermediate consumption of activity j (volume)
CTH_h :	Household h’s total consumption (value)
D_i :	Demand for domestic good i (volume)
DI_i,j :	Intermediate consumption of good i in activity j (volume)
DIT_i :	Intermediate demand for good i (volume)
DTF :	Receipts from direct taxation on firms’ income
DTH_h :	Receipts from direct taxation on household h’s income
EX_i :	Exports in good i (volume)
G :	Public expenditures
INV_i :	Investment demand for good i (volume)
IT :	Total investment
LD_j :	Activity j demand for labor (volume)
M_i :	Imports in good i (volume)
P_i :	Producer price of good i
PC_i :	Consumer price of composite good i
PD_i :	Domestic price of good i including taxes
PE_i :	Domestic price of exported good i
Pindex :	GDP deflator
Pinv :	Price index of investment
PL_i :	Domestic price of good i (excluding taxes)
PM_i :	Domestic price of imported good i
PV_j :	Value added price for activity j
Q_i :	Demand for composite good i (volume)
r_i :	Rate of return to capital in activity i
rl :	Rate of return to agricultural land
rc :	Rate of return to composite factor
SF :	Firms’ savings
SG :	Government’s savings
SH_h :	Household h’s savings
TI_i :	Receipts from indirect tax on i
TIE_i :	Receipts from tax on export i
TIM_i :	Receipts from import duties i
VA_j :	Value added for activity j (volume)
w :	Wage rate
XS_i :	Output of activity i (volume)
YDH_h :	Household h’s disposable income
YF :	Firms’ income
YG :	Government’s income
YH_h :	Household h’s income
LS :	Total labor supply (volume)
KD_i :	Demand for capital in activity i (volume)
CAB :	Current account balance
Ind_i,t :	Demand for capital in activity i (volume)
U_t :	Capital user cost
$C_{i, h}^{\min}$ :	Minimum consumption of good i by household h

C_i,h :	Household h’s consumption of good i (volume)
CF :	Composite agricultural capital-labor factor (volume)
CI_j :	Total intermediate consumption of activity j (volume)
CTH_h :	Household h’s total consumption (value)
D_i :	Demand for domestic good i (volume)
DI_i,j :	Intermediate consumption of good i in activity j (volume)
DIT_i :	Intermediate demand for good i (volume)
DTF :	Receipts from direct taxation on firms’ income
DTH_h :	Receipts from direct taxation on household h’s income
EX_i :	Exports in good i (volume)
G :	Public expenditures
INV_i :	Investment demand for good i (volume)
IT :	Total investment
LD_j :	Activity j demand for labor (volume)
M_i :	Imports in good i (volume)
P_i :	Producer price of good i
PC_i :	Consumer price of composite good i
PD_i :	Domestic price of good i including taxes
PE_i :	Domestic price of exported good i
Pindex :	GDP deflator
Pinv :	Price index of investment
PL_i :	Domestic price of good i (excluding taxes)
PM_i :	Domestic price of imported good i
PV_j :	Value added price for activity j
Q_i :	Demand for composite good i (volume)
r_i :	Rate of return to capital in activity i
rl :	Rate of return to agricultural land
rc :	Rate of return to composite factor
SF :	Firms’ savings
SG :	Government’s savings
SH_h :	Household h’s savings
TI_i :	Receipts from indirect tax on i
TIE_i :	Receipts from tax on export i
TIM_i :	Receipts from import duties i
VA_j :	Value added for activity j (volume)
w :	Wage rate
XS_i :	Output of activity i (volume)
YDH_h :	Household h’s disposable income
YF :	Firms’ income
YG :	Government’s income
YH_h :	Household h’s income
LS :	Total labor supply (volume)
KD_i :	Demand for capital in activity i (volume)
CAB :	Current account balance
Ind_i,t :	Demand for capital in activity i (volume)
U_t :	Capital user cost
$C_{i, h}^{\min}$ :	Minimum consumption of good i by household h

PWE_i :	World price of export i
PWM_i :	World price of import I
e :	Nominal Exchange rate (numéraire)

d_j :		Share of activity j in total value added
$l_{h}^{L}$ :		Share of land income received by household h
l^LF :		Share of land income received by firms
l^LROW :		Share of land income received by foreigners
$l_{h}^{R}$ :		Share of capital income received by household h
l^RF :		Share of capital income received by firms
l^ROW :		Share of capital income received by foreigners
$l_{h}^{W}$ :		Share of labour income received by household h
y_h :		Propensity to save
m_i :		Share of the value of good i in total investment
ng :		Population growth rate
d :		Capital depreciation rate
g_1i :		Parameter in the investment demand function
g_2i :		Parameter in the investment demand function
ir :	Real interest rate

A_j :	Scale coefficient (Cobb-Douglas production function)
aij_i,j :	Input-output coefficient
a_j :	Elasticity (Cobb-Douglas production function)
io_j :	Technical coefficient (Leontief production function)
v_j :	Technical coefficient (Leontief production function)

A_j :	Scale coefficient (Cobb-Douglas production function)
aij_i,j :	Input-output coefficient
a_j :	Elasticity (Cobb-Douglas production function)
io_j :	Technical coefficient (Leontief production function)
v_j :	Technical coefficient (Leontief production function)

$A_{i}^{K L}$ :	Scale coefficient
$a_{i}^{K L}$ :	Share parameter
$r_{i}^{K L}$ :	Substitution parameter
$s_{i}^{K L}$ :	Substitution elasticity

$A_{i}^{K L}$ :	Scale coefficient
$a_{i}^{K L}$ :	Share parameter
$r_{i}^{K L}$ :	Substitution parameter
$s_{i}^{K L}$ :	Substitution elasticity

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Abstract

Results from the Dynamic CGE Model of Bangladesh

Introduction

Static Module of the DCGE Model

Production bloc

Income and demand bloc

International Trade

Price blocs

Equilibrium Condition

Dynamic Module of the DCGE Model

The Bangladesh Social Accounting Matrix for 2006-07

Results of the DCGE Model and the Projections

Sectoral Growth Rates

Sectoral Shares in GDP

Sectoral Employment

Annex Description of the Variables and Parameters of the Dynamic CGE Model

Endogenous variables

Exogenous variables

Parameters

Production functions

CES function between capital and labor

CES function between skilled and unskilled labor

CES function between imports and domestic production

CET function between domestic production and exports

LES consumption function

Tax rates

Other parameters

Reference

Same Series

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International Labour Organization

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