Impacts of economic shocks on livestock in Iran: a DSGE model approach

Document Type : Original Research Article (Regular Paper)

Authors

1 Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran.

2 Monetary and Banking Research Academy, Tehran, Iran.

3 Department of Economics, Faculty of Economics and Management, Shahid Bahonar University of Kerman, Kerman, Iran.

Abstract

The objectives of this study is to investigate the responses of livestock economic variables (namely, output, consumption, prices, labor and capital) to changes in agricultural productivity, monetary, oil revenue and government spending (fiscal policy). To do so, a Dynamic Stochastic General Equilibrium (DSGE) model is constructed for Iran economy disaggregating livestock. Accordingly, the empirical results show that a rise in agricultural productivity results in rising livestock output consumption, hours worked and capital and falling price index. In response to positive monetary shock all the variables increase. Livestock consumption and prices rise following by positive oil revenue shock. However, output, employment, capital and real wages initially fall and rise 3-4 quarters after shock occurrence suggesting the symptoms of Dutch Disease in Iran’s agriculture. Government spending shock leads to an increase in the output, consumption, hours and prices and a decrease in capital. To sum up with, the findings reveal agricultural productivity shock has the strongest effects on livestock subsector when compared to those of other shocks. The negative effects of oil revenue shock are more than those of other shocks and we see the weakest responses under monetary and government spending shocks.

Keywords

Main Subjects

References

  • Aadland, D., 2002. Cattle cycles, heterogeneous expectations and the age distribution of capital. Journal of Economic Dynamics and Control 28, 1977-2002.
  • Allegret, J.P., Benkhodja, M.T., 2015. External shocks and monetary policy in an oil exporting economy. Journal of Policy Modeling 37, 652–667.
  • Alpanda, S., Aysun, U., 2014. International transmission of financial shocks in an estimated DSGE model. Journal of International Money and Finance 47, 21-55.
  • Bakhtiari, S., Haghi, Z., 2001. The survey of effects of oil revenues increase on agriculture sector: Dutch Disease in Iran (In Persian). Agricultural Economy and Development 35, 109-139.
  • Benkhodja, M.T., 2011. Monetary policy and the Dutch Disease in a small open oil exporting economy. Working paper No. 1134, university of Lyon, France.
  • Calvo, G., 1983. Staggered prices in a utility-maximizing framework. Journal of Monetary Economics 12, 383-398.
  • Christiano, L., Martin, E., Charles, E., 2005. Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113, 1–45.
  • Daniel Ayalew, A., 2015. Household responses to shocks in rural Ethiopia: livestock as a buffer stock. Policy research working paper No. 7244, World Bank, Washington DC.
  • Dib, A., 2008. Welfare effects of commodity price and exchange rate volatilities in a multi-sector small open economy model. Working paper No. 2008-8, Bank of Canada.
  • Ghasabi Kohne Ghouchan, P., Lotfali Pour, M.R., Ahmadi, M.T., 2014. Investigation the influencing mechanisms & short term-long term dynamism impact of Iran’s oil revenues on value added in agriculture management. Asian Journal of Research in Business Economics and Management 10, 184-193.
  • Kurosaki, T., 2013. Dynamics of household assets and income shocks in the long-run process of economic development: the case of rural Pakistan. Asian Development Review 30, 76–109.
  • Manzour, D., Taghipour, A., 2015. Constructing a DSGE model for a small open oil exporting country: case study Iran (In Persian). Economic Policies and Researches 75, 7-44.
  • Mawejje, J., Holden, S.T., 2014. Social capital, shocks and livestock investments: evidence from Masaka District, Uganda. International Journal of Development 13, 98-112.
  • McPeak, J., 2004. Contrasting income shocks with asset shocks: livestock sales in northern Kenya. Oxford Economic Papers 56, 263–284.
  • Moyo, S., Swanepoel, F. J. C., 2010. Multi functionality of livestock in developing communities. In: Swanepoel, F. J. C., Stroebel, A., Moyo, S., The role of livestock in developing communities: enhancing multi functionality. Co-published by the technical centre for agricultural and rural cooperation and university of the Free State., South Africa, pp. 1-12.
  • Ngigi, M.W., Mueller, U., Birner, R., 2015. The role of livestock portfolios and group-based approaches for building resilience in the face of accelerating climate change: an asset-based panel data analysis from rural Kenya. Discussion papers on development policy No. 205, Center for Development Research, Bonn.
  • Nkang, N., Omonona, B., Yusu, S., Oni, O., 2013. Simulating the impact of exogenous food price shock on agriculture and the poor in Nigeria: results from a computable general equilibrium model. Sustainable Agriculture Research 1, 141-151.
  • Piri, M., Javidan, I., Faraji Dizji, S., 2011. An investigation on the effect of oil export changes on the growth of agriculture in Iran (In Persian). Journal of Economy and Development of Agriculture 3, 275-283.
  • Rosen, S., Murphy, K.M., Scheinkman, J.A., 1994. Cattle cycles. Journal of Political Economy 102, 468-492.
  • Safari, Kh., Salami, H., Daneshvar, Zh., 2010. Calculation of total factor productivity in agricultural sub-sectors (In Persian). M.Sc. Thesis, university of Tehran, Iran.
  • Smets, F., Wouters, R., 2003. An estimated dynamic stochastic general equilibrium model of the Euro area. Journal of the European Economics Association 1, 1123-1175.
  • Twine, E.E., Rude, J., Unterschultz, J., 2016. Canadian cattle cycles and market shocks. Canadian Journal of Agricultural Economics 64, 119-146.
  • Yun, T., 1996. Nominal price rigidity, money supply indigeneity and the business cycles. Journal of Monetary Economics 37, 345-370.
Journal of Livestock Science and Technologies
Volume 5, Issue 2
December 2017
Pages 75-85

Files

Share

How to cite

Statistics