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S T U D I E S & T O O L S

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Matlab Codes

Example of Monte Carlo Simulation (Not Economics) Simple use of a Monte Carlo simulation. Drawing random numbers from a uniform distribution to estimate the value of Pi = 3.14. [Go to the Example]

Simulation Kit for a Real Business Cycle Model This kit solves and simulates a typical real business cycle model. Euler equations are linearized around the steady state and a set of policy functions is found as a solution to a system of first-order difference equations. Response of the economy to a technology shock is calculated and plotted. A Monte-Carlo simulation displays second moments of replicated data in the model. Now Under Construction for Improvement * Ryo Kato (Bank of Japan)'s codes are good references for these codes. You can access his webpage here.

Joint Estimation of Impulse-Responses by Local Linear Projections This is for the paper titled "Estimation and Inference of Impulse Responses by Local Projections.", written by Professor Oscar Jorda at University of California, Davis. This kit is compatible with the Gauss code written by him: joint estimation of impulse-responses both by Local Linear Projection and VAR: implementation of joint hypothesis tests of impluse-response coefficients. For details about local linear projection, see the paper above. [DOWNLOAD]

Panel Data Analysis This provides a function, panel (x,y,t), which implements estimation of unobserved effects panel data models. The function estimates both fixed and random effect models and calculate Hausman test statistics to perform a hypothesis test on existence of a fixed effect. A sample program panelsample.m runs a Monte Carlo simulation of the estimation to demonstrate the performance of those methods. [DOWNLOAD] Working Papers "Idiosyncratic Technology Shocks, Business Cycles, and Stabilizing Interest Rate Rules" Abstract Empirical evidence has rejected the positive comovement among labor, output, and productivity in response to a technology shock, which is typically predicted by the Real Business Cycle (RBC) models. Incorporating idiosyncratic technology shocks into the model adds another insight into effects of technology shocks; an investment-specific shock initially slows down productivity, while a consumption-specific shock causes a modestly negative response of labor supply. Since a shock in one sector transmitted by a stabilizing monetary policy rule amplifies a fluctuation in the other, aggregate stabilization becomes costly when investment-specific shocks are dominant. Though not in straightforward ways, empirical evidence suggests the importance of the investment-specific shocks. [DOWNLOAD THE FULL TEXT] Published Papers "Implementability of the Non-Ricardian Optimal Fiscal Policy" The Kyoto Economic Review, Vol. 77, pp.1-19 (2008) Abstract Dealing with out-of-equilibrium behaviors of economic agents is necessary to fill in the gaps in the controversy surrounding the admissibility of the fiscal theory of the price level (FTPL). Incorporating Nash equilibrium into the theory serves this purpose. It turns out that under certain conditions, strategic interaction between a non-Ricardian benevolent government and households with tit-for-tat moves leads to an equilibrium consistent with the FTPL, where the non-Ricardian optimal fiscal policy is not globally viable. Implementability of the non-Ricardian policy depends on the stochastic properties of government expenditure, especially its variance. [LINK TO THE FULL TEXT] Conference and Workshops "Was Quantitative Easing Policy Effective? An Empirical Analysis of the Monetary Policy in Japan during 2001-2006 " (Joint Paper with Tsuyoshi Mihira, Nariyasu Yamasawa and Jun Saito) Presented at ESRI International Conference on September 14, 2006 [LINK TO THE RELATED PAGE] [Back to Home]