In this paper, we examine the role of global and domestic credit supply shocks in macroeconomic fluctuations for Emerging Markets. For this purpose, we impose a set of zero and sign restrictions within a medium-scale Bayesian Vector Auto-Regressive model. Quarterly data from South Africa and G-7...

Our goal is to examine the income inequality and welfare effects of the direct distribution of resource rents and subsequent taxation in Iran. We use rich micro survey data covering more than 36,000 Iranian households in 2009. Our micro-simulations show that the direct distribution of resource...

In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a...

We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating...

We use Bayesian Model Averaging (BMA) to evaluate the robustness of determinants of economic growth in a new dataset of 255 European regions in the 1995-2005 period. We use three different specifications based on (1) the cross-section of regions, (2) the cross-section of regions with country...

Accurate poverty measurement relies on household consumption data, but such data are often inadequate, outdated or display inconsistencies over time in poorer countries. To address these data challenges, we employ survey-to-survey imputation to produce estimates for several poverty indicators...

Poverty maps are a useful tool for the targeting of social programs on areas with high concentrations of poverty. However, a static focus on poverty ignores the temporal dimension of poverty. Thus, current nonpoor households still face substantial welfare volatility and are at risk of becoming...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

We postulate a nonlinear DSGE model with a financial sector and heterogeneous households. In our model, the interaction between the supply of bonds by the financial sector and the precautionary demand for bonds by households produces significant endogenous aggregate risk. This risk induces an...