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Economic uncertainty and growth performance: a macroeconomic modeling analysis for Pakistan


This paper investigates the effects of economic uncertainty on growth performance of Pakistan through developing a small macroeconomic model. The GARCH method has been used for construction of economic uncertainty variables related to macroeconomic policies. The structural outcomes clearly indicate that economic policy uncertainty affects negatively on real and nominal sectors of Pakistan. The forecasting of model and different policy uncertainty simulation shocks also indicated that an adjustment in economic policies due to change of policy objectives create uncertain environment in country, which not only deteriorates the investment climate of country, it also affects the economic growth. Our study concludes that economic uncertainty not only reduces the current investment and economic growth, it also affects the future decision of investment and economic growth. This study suggests that sustainable and steady economic policies always reduce economic uncertainty and promote the confidence of economic agents, which help in achieving the targets of investment, trade and economic growth. Our study also maintains the predictability and reliability of government policies for the accomplishment of macroeconomic goals and economic development of country.

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Fig. 1


  1. See Varvarigos (2004).

  2. The authors constructed a macroeconomic model for OECD countries.

  3. For the monetary policy, we used real interest rate uncertainty, private sector credit and inflation uncertainty in the equation, for the trade policy, uncertainty directly linked to imports and exchange rate is used, whereas for the fiscal policy uncertainty related to government budget borrowing, tax rate and government development expenditures is used.

  4. The present macroeconomic model is a small, compact and highly aggregate macro model.

  5. Their uncertainty—investment analysis depends upon the assumption that investment is characterized by irreversibility and fluctuates between the low and high tax regimes’ policies of government.

  6. Data of 138 countries was collected from Barro Lee data set. (1994) available at NBER website.

  7. The sample size of the study is 94 countries for the period 1970–1995.

  8. Three related to the macroeconomic environment and aggregate profitability of capital-growth, inflation and the relative price of investment goods and another two more closely related to the relative profitability of different economic sectors the terms of trade and the real exchange rate.

  9. The author divided overall data set into five sub periods. Each period contain five years data except last sub period. Last sub period includes 7 years data. The aim behind division of this data set is to use the GARCH method to measurement of uncertainty variables.

  10. The authors estimated reduced form equation to explore the possible effects of uncertainty on investment and economic growth and assumed that all countries acquired a common production structure. In a cross country studies they used output variable as estimate of uncertainty variable and check whether the uncertainty of output effect the investment decision of countries.

  11. Their sample includes nine developed and nine developing countries.

  12. The authors found that the uncertainty at highest frequency is largest.

  13. The author used monthly data of Colombian economy for the period 1980–2003.

  14. The sample period started 1850 for Germany, 1860 for the US, and 1874 for Japan to 1999.

  15. Pasha et al. (1995) model is an integrated social policy macroeconomic model (ISPM), which evidently shows the relationship between macroeconomic performance and social sector development.

  16. Their model comprising of 17 equations, out of which 11 are behavioral equations while the rest are either identities or definitional equations.

  17. This model comprises of 21 equations, out of which 13 are behavioral and the rest are identities.

  18. Agriculture has strong linkage with rest of the economy by providing raw material to downstream industry and contributing substantially to national exports. In Pakistan, there is no agriculture tax, thats why uncertainty regarding fiscal policy variable is not used in agriculture equation.

  19. The industrial sector includes the production of manufacturing, mining and quarrying, construction, electricity and gas distribution. The service sector is composed of tertiary activities includes transport, communication, storage, whole sale, retail trade, finance, insurance, dwelling ownership, public admin, defense and social and community service.

  20. According to the Keynesian absolute-income hypothesis, the disposable income is assumed to have a positive influence on private consumption. Later theories, such as the life-cycle or the permanent-income hypothesis introduced other explanatory factors like the real interest rate or the inflation rate, whose impact is not clear a priori.

  21. The government development expenditures provides basic infrastructure to the private sector.

  22. The policy makers frequently advocated that public investment harmonized the private investment instead of crowding out of private sector in developing countries like Pakistan.

  23. With higher-income levels, investors would tend to shift more of their wealth to finance investment and high interest rate increases the cost of capital and reduces profitability of private sector.

  24. The formula of average direct tax rate and indirect tax rate is used as suggested by Tjipe et al. (2004).

  25. Nominal GDP used as proxy of economic activities. The non tax revenue includes the profits of post offices/Pakistan Telecommunication Authority, interest, dividend, transfer of State Bank of Pakistan, defense, development surcharge on gas, discount retained on crude oil, royalties on gas and others etc.

  26. This also discussed in investment block as public investment.

  27. The unit value of exports to domestic price is used to reveal the effects of relative price. (For detail see Atique and Ahmad 2003; Chaudhary and Shabbir 2005).

  28. Real GDP is used as the proxy of capacity utilization and wage rate as a proxy of cost of production in all equation. (For more detail, see Atique and Ahmad 2003).

  29. As the private sector credit increases, the investment of private sector raises, which further increases the import demand of capital goods.

  30. Government budget deficit provides an important mechanism for providing monetary base in Pakistan.

  31. Others measures are the 5 years moving average or 5 years moving standard deviation etc were also used to proxy uncertainty (Goel and Ram 2001).

  32. Water is key input for agriculture sector. Any natural calamity regarding water which increases or decreases the water supply compare to requirement may reduces the agriculture output. Moreover, the uncertainty regarding monetary policy affects the availability of agriculture credit.

  33. The highest difference between the coefficient of marginal propensity to consume and autonomous consumption also support the findings of Ra and Rhee (2005) and Khan and Din (2011).

  34. It may reflect the situation that as income increases; private investment in these sectors also increases but the structural transformation of economy from agriculture to strong industrial base or service sector requires technological innovation and product diversification.

  35. Inflation hurt the poor more as compare to rich due to narrow tax base. According to some experts, inflation is cruelest for poor.

  36. High cost of production increases always deteriorates the international competitiveness of Pakistan.

  37. As imports prices increases relative to domestic prices, the import demand clearly decline.

  38. This indicated that as uncertainty increases the money supply also increases.

  39. Theil’s inequality coefficient compares the forecast with the random walk and always lies between zero (i.e. zero indicate perfect fit) and one (i.e. forecast is not better than that of the random walk).

  40. The MAPE is not normalized test but it coefficient should be as smaller as possible. If MAPE is between zero and 10, it’s mean it is very good for forecasting (Green 2003; Tjipe et al. 2004).

  41. The graphs clearly indicated that the responses of each endogenous variable are in line with the expected signs and also tracking the policy shock in equal magnitude.

  42. The reason of low availability is lack of storage facility in Pakistan. The reason of private sector low formation is lack of infrastructure particularly in rural areas and lack of government support to agriculture sector in Pakistan.

  43. Currently the capital formation in industrial sector and service sector is at its lower level due to political instability and bad law and order condition.

  44. The reason behind the increase in government consumption may be increase in government borrowing from banks to finance the budget.

  45. The high level of inflation and lowering of average tax to GDP ratio in Pakistan also significantly contributed towards the declining of revenue.

  46. This reason of this growth may be the highest government borrowing for financing the budget deficit due to lowering of revenue collection.

  47. All simulations are carried out without any policy rules. With the policy simulation, we can measure the time paths of counterfactual effects of uncertainty due to change in policy variables on macroeconomic indicators.

  48. The output of industrial sectors effects due to imports of capital goods and raw material.

  49. This indicated negative effects on economic activity.


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Correspondence to Amber Fatima.

Appendix I

Appendix I

Equations of the Model

Behavioral equations

Production block:


\(\text{ Y }_{AGR} =\beta _0 +\beta _1 CAP_{AGR} +\beta _2 AW+\beta _3 INF+\beta _4 LAB_{AGR} +\beta _5 UAW+\beta _6 URT+\varepsilon \)


\(\text{ Y }_{IND} =\beta _7 +\beta _8 CAP_{IND} +\beta _9 Y_{AGR} +\beta _{10} IRM+\beta _{11} INF+\beta _{12} LAB_{IND} +\beta _{13} URT+\beta _{14} UER+\beta _{15} UTAX+\varepsilon _2 \)


\(\text{ Y }_{SER} =\beta _{16} +\beta _{17} LAB_{SER} +\beta _{18} CAP_{SER} +\beta _{19} YA+\beta _{20} URT+\beta _{21} UTAX+\varepsilon _3 \)

Consumption block


\(PCE=\beta _{22} +\beta _{23} YD+\beta _{24} UWR+\beta _{25} UTAX+\varepsilon _4 \)

Investment block


\(PI_{AGR} =\beta _{26} +\beta _{27} RT+\beta _{28} Y_{AGR} +\beta _{29} GDE+\beta _{30} URT+\beta _{31} UGDE+\varepsilon _5 \)


\(PI_{IND} =\beta _{32} +\beta _{33} RT+\beta _{34} Y_{IND} +\beta _{35} GDE+\beta _{36} UTAX+\beta _{37} URT+\beta _{38} UGDE+\varepsilon _6 \)


\(PI_{SER} =\beta _{39} +\beta _{40} RT+\beta _{41} Y_{SER} +\beta _{42} GDE+\beta _{43} UGDE+\beta _{44} UTAX+\beta _{45} URT+\varepsilon _7 \)

Government block


\(DTR=\beta _{46} +\beta _{47} NGDP+\beta _{48} ADTR+\beta _{49} GDPDEF+\beta _{50} UTAX+\beta _{51} UGDPDEF+\varepsilon _8 \)


\(IDTR=\beta _{52} +\beta _{53} NGDP+\beta _{54} AIDTR+\beta _{55} GDPDEF+\beta _{56} IMPORT+\beta _{57} UIMP+\beta _{58} UGDPDEF+\varepsilon _9 \)


\(NTXR=\beta _{59} +\beta _{60} NGDP+\beta _{61} URT+\beta _{62} UGDPDEF+\beta _{63} UGDE+\varepsilon _{10} \)


\(GCE=\beta _{64} +\beta _{65} GDE+\beta _{66} TXR+\beta _{67} GDPDEF+\beta _{68} UTAX+\beta _{69} UGDE+\varepsilon _{11} \)

Trade block


\(EXP_P =\beta _{70} +\beta _{71} (UNIPRI/GDPDEF)+\beta _{72} ER+\beta _{73} WAGE+\beta _{74} YA+\beta _{75} UER+\beta _{76} UGDPDEF+\varepsilon _{12} \)


\(EXP_{MAN} =\beta _{73} +\beta _{77} (UNIMAN/GDPDEF)+\beta _{78} WAGE+\beta _{79} YA+\beta _{80} ER+\beta _{80} UER+\beta _{81} UGDPDEF+\varepsilon _{13} \)


\(EXP_{SM} =\beta _{82} +\beta _{83} (UNISM/GDPDEF)+\beta _{84} ER+\beta _{85} WAGE+\beta _{86} YA+\beta _{87} UGDPDEF+\beta _{88} UER+\varepsilon _{14} \)


\(IMP_{CON} =\beta _{89} +\beta _{90} (UNICON/GDPDEF)+\beta _{91} ER+\beta _{92} YA+\beta _{93} UER+\beta _{94} UTAX+\varepsilon _{15} \)


\(IMP_{CAP} =\beta _{95} +\beta _{96} (UNICAP/GDPDEF)+\beta _{97} ER+\beta _{98} YA++\beta _{99} PSC+\beta _{100} UPSC+\beta _{101} UER+\varepsilon _{16} \)

Monetary block


\(MS=\beta _{102} +\beta _{103} GBNB+\beta _{104} TFR+\beta _{105} PSC+\beta _{106} UGBNB+\beta _{107} UPSC+\varepsilon _{17} \)


\(GDPDEF=\beta _{108} +\beta _{109} MS+\beta _{110} RT+\beta _{111} PF+\beta _{112} YA+\beta _{113} UPF+\beta _{114} URT+\varepsilon _{18} \)



\(\text{ Y } A=Y_{AGR} +Y_{IND} +Y_{SER} \)






\(PI=PI_{AGR} +PI_{IND} +PI_{SER} \)

















Description of endogenous variable





Gross domestic product on 2000–2001 Prices

Rs. Million

\(\text{ Y }_\mathrm{AGR}\)

Production of agriculture on 2000–2001 Prices

\(\text{ Y }_\mathrm{IND}\)

Production of industries on 2000–2001 Prices

\(\text{ Y }_\mathrm{SER}\)

Production of services sector on 2000–2001 Prices

\(\text{ PI }_\mathrm{AGR}\)

Private investment to agriculture sector on 2000–2001 Prices

\(\text{ PI }_\mathrm{IND}\)

Private investment to industrial sector on 2000–2001 Prices

\(\text{ PI }_\mathrm{SER}\)

Private investment to service sector on 2000–2001 Prices


Nominal GDP


Total Exports on 2000–2001 prices

\(\text{ EXP }_\mathrm{P}\)

Exports of primary commodity on 2000–2001 Prices

\(\text{ EXP }_\mathrm{SM}\)

Exports of semi manufactured goods on 2000–2001 Prices

\(\text{ EXP }_\mathrm{MAN}\)

Exports of manufactured goods on 2000–2001 Prices


Total Imports on 2000-2001 Prices

\(\text{ IMP }_\mathrm{CAP}\)

Imports of capital goods on 2000–2001 Prices

\(\text{ IMP }_\mathrm{CON}\)

Imports of consumer goods on 2000–2001 Prices


Total revenue collection


Tax revenue


Non tax revenue


Direct tax revenue


Indirect tax revenue


Gross government expenditures


Government consumption expenditure


Personal disposable income on 2000–2001 prices


Budget deficit


Money supply


Private consumption expenditure on 2000–2001 prices


Net exports


GDF deflator


Description of exogenous variable




\(\text{ CAP }_\mathrm{AGR}\)

Investment in agriculture sector on 2000-2001 Price

Rs. Million

\(\text{ CAP }_\mathrm{IND}\)

Investment in industrial sector on 2000-2001 Prices

\(\text{ CAP }_\mathrm{SER}\)

Investment in service sector on 2000-2001 Prices


Availability of Water



Infrastructure (Roads length use as proxy of infrastructure)



Interest rate (weighted average rate of return on advances)



Exchange rate

Rs. Per US$


Workers’ remittances

Rs. Million


Average daily wage of skilled labor in Karachi

Pakistani Rs.


(proxy for cost of production)



Price of foreign goods (2005 base year)



Total foreign reserves

US$ billion


Unit value index of Exports primary commodities



Unit value index of Exports of manufactured goods


Unit value index of Exports of semi manufactured goods


Unit value index of Imports of capital goods


Unit value index of Imports of consumer goods


Government budget deficit financing borrowing

Rs. Million


Import of raw material on 2000-2001 Prices


Government development expenditure

\(\text{ LAB }_\mathrm{AGR}\)

Labor force in agriculture sector


\(\text{ LAB }_\mathrm{IND}\)

Labor force in industrial sector


\(\text{ LAB }_\mathrm{SER}\)

Labor force in service sector



Nominal GDP

Rs. Million


Banks credit to private sector


Uncertainty related to availability of water



Uncertainty related to GDP deflator



Uncertainty related to exchange rate



Uncertainty related to private sector credit



Uncertainty related to workers’ remittances



Uncertainty related to tax revenue



Uncertainty related to government borrowing for budgetary support



Uncertainty related to government development expenditures



Uncertainty related to imports



Uncertainty related to foreign inflation



Uncertainty related to interest rate


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Fatima, A., Waheed, A. Economic uncertainty and growth performance: a macroeconomic modeling analysis for Pakistan. Qual Quant 48, 1361–1387 (2014).

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  • Policy
  • Uncertainty
  • Growth
  • Macroeconomic Model
  • Forecasting
  • Simulation
  • Pakistan