Do institutions matter for economic fluctuations? Weak property rights in a business cycle model for Mexico

This paper shows that introducing weak property rights in the standard real business cycle (RBC) model can help to explain economic fluctuations. This is motivated by the empirical observation that changes in institutions in emerging markets are related to the evolution of the main macroeconomic variables. In particular, in Mexico, the movements in productivity in the data are associated with changes in institutions, so that we can explain productivity shocks to a large extent as shocks to the quality of institutions. We find that the model with shocks to the degree of protection of property rights only - without technology shocks - can match the second moments in the data for Mexico well. In particular, the fit is better than that of the standard neoclassical model with full protection of property rights regarding the auto-correlations and cross-correlations in the data, especially those related to labor. Viewing productivity shocks as shocks to institutions is also consistent with the stylized fact of falling productivity and non-decreasing labor hours in Mexico over 1980-1994, which is a feature that the neoclassical model cannot match.

Financial shocks and the US business cycle

Employing the financial accelerator (FA) model of Bernanke, Gertler and Gilchrist (1999) enhanced to include a shock to the FA mechanism, we construct and study shocks to the efficiency of the financial sector in post-war US business cycles. We find that financial shocks are very tightly linked with the onset of recessions, more so than TFP or monetary shocks. The financial shock invariably remains contractionary for sometime after recessions have ended. The shock accounts for a large part of the variance of GDP and is strongly negatively correlated with the external finance premium. Second-moments comparisons across variants of the model with and without a (stochastic) FA mechanism suggests the stochastic FA model helps us understand the data.

Structural Interactions in Spatial Panels

Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important distinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability assumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.

Understanding Interactions in Social Networks and Committees

While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

Ordering Policy Rules with an Unconditional Welfare Measure

The unconditional expectation of social welfare is often used to assess alternative macroeconomic policy rules in applied quantitative research. It is shown that it is generally possible to derive a linear - quadratic problem that approximates the exact non-linear problem where the unconditional expectation of the objective is maximised and the steady-state is distorted. Thus, the measure of pol icy performance is a linear combinat ion of second moments of economic variables which is relatively easy to compute numerically, and can be used to rank alternative policy rules. The approach is applied to a simple Calvo-type model under various monetary policy rules.

Consumption Inequality and Discount Rate Heterogeneity

Although standard incomplete market models can account for the magnitude of the rise in consumption inequality over the life cycle, they generate unrealistically concave age pro.les of consumption inequality and unrealistically less wealth inequality. In this paper, I investigate the role of discount rate heterogeneity on consumption inequality in the context of incomplete market life cycle models. The distribution of discount rates is estimated using moments from the wealth distribution. I .nd that the model with heterogeneous income pro.les (HIP) and discount rate heterogeneity can successfully account for the empirical age pro.le of consumption inequality, both in its magnitude and in its non-concave shape. Generating realistic wealth inequality, this simulated model also highlights the importance of ex ante heterogeneities as main sources of life time inequality.