nep-cmp New Economics Papers
on Computational Economics
Issue of 2013‒08‒16
eight papers chosen by
Stan Miles
Thompson Rivers University

  1. Trade Liberalization and Productivity Growth: A Recursive Dynamic CGE Analysis for Turkey By Dudu, Hasan; Cakmak, Erol H.
  2. The impact of alternative input subsidy exit strategies on Malawi’s maize commodity market: By Mapila, Mariam A. T. J.
  3. Gdyn-E: a dynamic CGE model for the economic assessment of long run climate policy alternatives By Antimiani, A.; Costantini, V.; Martini, C.; Tommasino, M.C.
  4. Estimation Errors in Input-Output Tables and Prediction Errors in Computable General Equilibrium Analysis By Nobuhiro Hosoe
  5. Solving second and third-order approximations to DSGE models: A recursive Sylvester equation solution By Andrew Binning
  6. Trade openness and investment in North Africa: A CGE application to deep and comprehensive free trade areas (DCFTAs) between the EU and respectively Egypt, Morocco and Tunisia By Boulanger, P.; Kavallari, A.; Rau, M.L.; Rutten, M.
  7. Agriculture and adaptation in Bangladesh: Current and projected impacts of climate change: By Thomas, Timothy S.; Mainuddin, Khandaker; Chiang, Catherine; Rahman, Aminur; Haque, Anwarul; Islam, Nazria; Quasem, Saad; Sun, Yun
  8. Herding in financial markets: Bridging the gap between theory and evidence By Christopher Boortz; Simon Jurkatis; Stephanie Kremer; Dieter Nautz

  1. By: Dudu, Hasan; Cakmak, Erol H.
    Abstract: In this study, we analyze the effects of trade liberalization and productivity growth in agricultural activities on Turkey by using a dynamic CGE model calibrated to 2008 data. The simulation results suggest that Turkish economy is capable of accommodating the adverse effects of trade liberalization. There are significant welfare gains if trade liberalization is accompanied by the CAP payments in the accession scenario. Productivity increase in agri-food production by just decreasing food waste has prominent effects on welfare,trade and food security for the growing population.
    Keywords: Agricultural and Food Policy, International Relations/Trade, Production Economics, Productivity Analysis, Research Methods/ Statistical Methods,
    Date: 2013–06
  2. By: Mapila, Mariam A. T. J.
    Abstract: This study has been conducted in order to generate evidence of the visibility of exit from farm input subsidies in an African context. The study simulates the impact of alternative exit strategies from Malawi’s farm input subsidy program on maize markets. The simulation is conducted using a multiequation partial equilibrium model of the national maize market, which is sequentially linked via a price-linkage equation to local rural maize markets. The model accounts for market imperfections prevailing in the country that arise from government price interventions. Findings show that some alternative exit strategies have negative and sustained impacts on maize yields, production, and acreage allocated to maize over the simulation period. Market prices rise steadily as a result of the implementation of different exit strategies. Despite higher maize prices, domestic maize consumption remains fairly stable, with a slow but increasing trend over the simulation period.
    Keywords: fertilizer subsidies, farm input allocation, subsidy reform, partial equilibrium model, Agricultural policies, maize,
    Date: 2013
  3. By: Antimiani, A.; Costantini, V.; Martini, C.; Tommasino, M.C.
    Keywords: Agricultural and Food Policy, Environmental Economics and Policy, Research Methods/ Statistical Methods,
    Date: 2013–06
  4. By: Nobuhiro Hosoe (National Graduate Institute for Policy Studies)
    Abstract: We used 1995-2000-2005 linked input-output (IO) tables for Japan to examine estimation errors of updated IO tables and the resulting prediction errors in computable general equilibrium (CGE) analysis developed with updated IO tables. As we usually have no true IO tables for the target year and therefore need to estimate them, we cannot evaluate estimation errors of updated IO tables without comparing the updated ones with true ones. However, using the linked IO tables covering three different years enables us to make this comparison. Our experiments showed that IO tables estimated with more detailed and recent data contained smaller estimation errors and led to smaller quantitative prediction errors in CGE analysis. Despite the quantitative prediction errors, prediction was found to be qualitatively correct. As for the performance of updating techniques of IO tables, a cross-entropy method often outperformed a least-squares method in IO estimation with only aggregate data for the target year but did not necessarily outperform the least-squares method in CGE prediction.
    Date: 2013–08
  5. By: Andrew Binning (Norges Bank (Central Bank of Norway))
    Abstract: In this paper I derive the matrix chain rules for solving a second and a third-order approximation to a DSGE model that allow the use of a recursive Sylvester equation solution method. In particular I use the solution algorithms of Kamenik (2005) and Martin & Van Loan (2006) to solve the generalised Sylvester equations. Because I use matrix algebra instead of tensor notation to find the system of equations, I am able to provide standalone Matlab routines that make it feasible to solve a medium scale DSGE model in a competitive time. I also provide Fortran code and Matlab/Fortran mex files for my method.
    Keywords: Solving dynamic models, Second-order approximation, Third-order appeoximation, Second-order matrix chain rule, Third-order matrix chain rule, Generalised Sylvester equations
    Date: 2013–08–05
  6. By: Boulanger, P.; Kavallari, A.; Rau, M.L.; Rutten, M.
    Keywords: Food Security and Poverty, International Relations/Trade, Public Economics,
    Date: 2013–06
  7. By: Thomas, Timothy S.; Mainuddin, Khandaker; Chiang, Catherine; Rahman, Aminur; Haque, Anwarul; Islam, Nazria; Quasem, Saad; Sun, Yun
    Abstract: The goal of this research was to examine the likely impacts of climate change on agriculture in Bangladesh, and develop recommendations to policymakers to help farmers adapt to the changes. In this study, we use climate data from four general circulation models (GCMs) to evaluate the impact of climate change on agriculture in Bangladesh by 2050. We use the DSSAT (Decision Support System for Agrotechnology Transfer) crop modeling software to evaluate crop yields, first for the 1950 to 2000 period (actual climate) and then for the climates given by the four GCMs for 2050. We evaluate crop yields at 1,789 different points in Bangladesh, using a grid composed of roughly 10 kilometer (km) squares, for 8 different crops in 2000 and 2050. For each crop, we search for the best cultivar (variety) at each square, rather than limiting our analysis to a single variety for all locations. We also search for the best planting month in each square. In addition, we explore potential gains in changing fertilizer levels and in using irrigation to compensate for rainfall changes. This analysis indicates that when practiced together, using cultivars better suited for climate change and adjusting planting dates can lessen the impacts of climate change on yields, especially for rice, and in some cases actually result in higher yields. In addition, the analysis shows that losses in yield due to climate change can be compensated for, for many crops, by increasing the availability of nitrogen in the soil.
    Keywords: Climate change, Impact model, Adaptation, Agricultural productivity, Crop yields, Varieties,
    Date: 2013
  8. By: Christopher Boortz; Simon Jurkatis; Stephanie Kremer; Dieter Nautz
    Abstract: Due to data limitations and the absence of testable, model-based predictions, theory and evidence on herd behavior are only loosely connected. This paper attempts to close this gap in the herding literature. From a theoretical perspective, we use numerical simulations of a herd model to derive new, theory-based predictions for aggregate herding intensity. From an empirical perspective, we employ high-frequency, investor-specic trading data to test the theory-implied impact of information risk and market stress on herding. Conrming model predictions, our results show that herding intensity increases with information risk. In contrast, herding measures estimated for the nancial crisis period cannot be explained by the herd model. This suggests that the correlation of trades observed during the crisis is mainly due to the common reaction of investors to new public information and should not be misinterpreted as herd behavior.
    Keywords: Herd Behavior, Institutional Trading, Model Simulation
    JEL: G11 G24
    Date: 2013–07

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