How the global perspective can help us identify structural shocks
This paper argues that global perspective can help us with the identification of structural shocks by utilizing the information on the signs of the responses of individual countries (cross section units). We demonstrate the main idea by means of Monte Carlo experiments and present an empirical application where we look at the effects of oil supply shocks on output and on global exchange rate constellation. Using a large-scale GVAR model of oil prices and the global economy, we find supply shocks tend to have a stronger impact on emerging economies' real output as compared with mature ...
Early Mandated Social Distancing Does Best to Control COVID–19 Spread
Voluntary social distancing and a lack of compliance with mandated polices have led to unnecessarily high infection rates and death tolls in a number of countries.
A multi-country approach to forecasting output growth using PMIs
This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence of a strong unobserved common factor can lead to an undetermined GVAR model. To solve this problem, we propose augmenting the GVAR with additional proxy equations for the strong factors and establish conditions under which forecasts from the augmented GVAR model (AugGVAR) uniformly converge in probability (as the panel dimensions N,T? ? such that N/T?? for some 0
Debt, inflation and growth robust estimation of long-run effects in dynamic panel data models
This paper investigates the long-run effects of public debt and inflation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic heterogeneous panel data models with cross-sectionally dependent errors. The relative merits of the CS-DL approach and other existing approaches in the literature are discussed and illustrated with small sample evidence obtained by means of Monte Carlo simulations. On the empirical side, using data on a ...
Mean Group Estimation in Presence of Weakly Cross-Correlated Estimators
This paper extends the mean group (MG) estimator for random coefficient panel data models by allowing the underlying individual estimators to be weakly cross-correlated. Weak cross-sectional dependence of the individual estimators can arise, for example, in panels with spatially correlated errors. We establish that the MG estimator is asymptotically correctly centered, and its asymptotic covariance matrix can be consistently estimated. The random coefficient specification allows for correct inference even when nothing is known about the weak cross-sectional dependence of the errors. This is ...
Liquidity, risk and the global transmission of the 2007–08 financial crisis and the 2010–11 sovereign debt crisis title
The paper analyses the transmission of liquidity shocks and risk shocks to global financial markets. Using a Global VAR methodology, the findings reveal fundamental differences in the transmission strength and pattern between the 2007?08 financial crisis and the 2010?11 sovereign debt crisis. Unlike in the former crisis, emerging market economies have become much more resilient to adverse shocks in 2010?11. Moreover, a fight-to-safety phenomenon across asset classes has become particularly strong during the 2010?11 sovereign debt crisis, with risk shocks driving down bond yields in key ...
A simple model of price dispersion
This article considers a simple stock-flow matching model with fully informed market participants. Unlike in the standard matching literature, prices are assumed to be set ex-ante. When sellers pre-commit themselves to sell their products at an advertised price, the unique equilibrium is characterized by price dispersion due to the idiosyncratic match payoffs (in a marketplace with full information). This provides new insights into the price dispersion literature, where price dispersion is commonly assumed to be generated by a costly search of uninformed buyers.
Spatial considerations on the PPP debate
This paper studies the influence of aggregating across space when (i) testing the PPP theory or more generally pair-wise cointegration and (ii) evaluating the PPP puzzle. Our contribution is threefold: we show that aggregating foreign data and applying an ADF test may lead to erroneously reject the PPP hypothesis. We then show, on the basis of theoretical arguments as well as Monte Carlo experiments, that a sizable bias in the estimates of half-life deviations to PPP may be due to the effect of aggregation across space. We finally illustrate empirically the importance of spatial ...
The perils of aggregating foreign variables in panel data models
The curse of dimensionality refers to the difficulty of including all relevant variables in empirical applications due to the lack of sufficient degrees of freedom. A common solution to alleviate the problem in the context of open economy models is to aggregate foreign variables by constructing trade-weighted cross-sectional averages. This paper provides two key contributions in the context of static panel data models. The first is to show under what conditions the aggregation of foreign variables (AFV) leads to consistent estimates (as the time dimension T is fixed and the cross section ...
Aggregation in large dynamic panels
This paper investigates the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is derived and used (i) to establish conditions under which Granger's (1980) conjecture regarding the long memory properties of aggregate variables from "a very large scale dynamic, econometric model" holds, and (ii) to show which distributional features of micro parameters can be identified from ...