Search Results
Working Paper
Long-run effects in large heterogenous panel data models with cross-sectionally correlated errors
This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T) and the crosssection dimension (N) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL type estimator, the CS-DL ...
Working Paper
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 ...
Working Paper
Big data analytics: a new perspective
Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique used to trade off parsimony and fit when the number of possible covariates is large, often much larger than the number of available observations. However, issues such as the choice of a penalty function and tuning parameters associated with the use ...
Working Paper
Country-specific oil supply shocks and the global economy: a counterfactual analysis
This paper investigates the global macroeconomic consequences of country-specific oilsupply shocks. Our contribution is both theoretical and empirical. On the theoretical side, we develop a model for the global oil market and integrate this within a compact quarterly model of the global economy to illustrate how our multi-country approach to modelling oil markets can be used to identify country-specific oil-supply shocks. On the empirical side, estimating the GVAR-Oil model for 27 countries/regions over the period 1979Q2 to 2013Q1, we show that the global economic implications of oil-supply ...
Working Paper
Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels
Using a transformation of the autoregressive distributed lag model due to Bewley, a novel pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics is proposed. The PB estimator is directly comparable to the widely used Pooled Mean Group (PMG) estimator, and is shown to be consistent and asymptotically normal. Monte Carlo simulations show good small sample performance of PB compared to the existing estimators in the literature, namely PMG, panel dynamic OLS (PDOLS) and panel fully-modified OLS (FMOLS). Application of two bias-correction ...
Working Paper
Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe
This paper provides estimates of COVID-19 transmission rates and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government-mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicates that the diversity of outcomes that we document may have resulted from the non-linear interaction of mandated and voluntary social distancing and the economic incentives that governments provided to support isolation. The importance of these ...
Working Paper
Half-panel jackknife fixed effects estimation of panels with weakly exogenous regressor
This paper considers estimation and inference in fixed effects (FE) panel regression models with lagged dependent variables and/or other weakly exogenous (or predetermined) regressors when NN (the cross section dimension) is large relative to TT (the time series dimension). The paper first derives a general formula for the bias of the FE estimator which is a generalization of the Nickell type bias derived in the literature for the pure dynamic panel data models. It shows that in the presence of weakly exogenous regressors, inference based on the FE estimator will result in size distortions ...
Journal Article
Rising Public Debt to GDP Can Harm Economic Growth
The debt?growth relationship is complex, varying across countries and affected by global factors. While there is no simple universal threshold above which debt to GDP significantly depresses growth, high and rising public debt burdens slow growth in the long term, data from the past four decades indicate.
Working Paper
Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels
This paper, using the Bewley (1979) transformation of the autoregressive distributed lag model, proposes a pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics, in the same setting as the widely used Pooled Mean Group (PMG) estimator. The Bewley transform enables us to obtain an analytical closed form expression for the PB, which is not available when using the maximum likelihood approach. This lets us establish asymptotic normality of PB as n,Tââ jointly, allowing for applications with n and T large and of the same order of ...
Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks
This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signal variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of ...