A time-space dynamic panel data model with spatial moving average errors

This paper focuses on the estimation and predictive performance of several estimators for the time-space dynamic panel data model with Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. A dynamic spatial Generalized Moments (GM) estimator is proposed which combines the approaches proposed by Baltagi, Fingleton and Pirotte (2014) and Fingleton (2008). The main idea is to mix non-spatial and spatial instruments to obtain consistent estimates of the parameters. Then, a forecasting approach is proposed and a linear predictor is derived. Using Monte Carlo simulations, we compare the short-run and long-run e¤ects and evaluate the predictive effficiencies of optimal and various suboptimal predictors using the Root Mean Square Error (RMSE) criterion. Last, our approach is illustrated by an application in geographical economics which studies the employment levels across 255 NUTS regions of the EU over the period 2001-2012, with the last two years reserved for prediction

Forecasting with Unbalanced Panel Data

This paper derives the best linear unbiased prediction (BLUP) for an unbalanced panel data model. Starting with a simple error component regression model with unbalanced panel data and random effects, it generalizes the BLUP derived by Taub (1979) to unbalanced panels. Next it derives the BLUP for an unequally spaced panel data model with serial correlation of the AR(1) type in the remainder disturbances considered by Baltagi and Wu (1999). This in turn extends the BLUP for a panel data model with AR(1) type remainder disturbances derived by Baltagi and Li (1992) from the balanced to the unequally spaced panel data case. The derivations are easily implemented and reduce to tractable expressions using an extension of the Fuller and Battese (1974) transformation from the balanced to the unbalanced panel data case

Does Hospital Competition Improve Efficiency? The Effect of the Patient Choice Reform in England

We use the 2006 relaxation of constraints on patient choice of hospital in the English NHS to investigate the effect of hospital competition on dimensions of efficiency including indicators of resource management (admissions per bed, bed occupancy rate, proportion of day cases, and cancelled elective operations) and costs (reference cost index for overall and elective activity, cleaning services costs, laundry and linen costs). We employ a quasi differences-in-differences approach and estimate seemingly unrelated regressions and unconditional quantile regressions with data on hospital trusts from 2002/03 to 2010/11. Our findings suggest that increased competition had mixed effects on efficiency. An additional equivalent rival increased admissions per bed by 1.1%, admissions per doctor by 0.9% and the proportion of day cases by 0.38 percentage points, but it also increased the number of cancelled elective operations by 2.5%

The influence of government ideology on monetary policy:New cross-country evidence based on dynamic heterogeneous panels

Using data of 23 OECD countries over the 1980–2005 period, we examine whether government ideology affects monetary policy, conditional on central bank independence. Unlike previous studies in this line of literature, we estimate central bank behavior using forward‐looking and real‐time data in Taylor rule models and use estimators that allow for heterogeneity across countries. Our models with heterogeneous slope coefficients for the full sample do not suggest partisan effects. We also do not find evidence that central bank behavior is conditioned by the interaction of the ideology of the incumbent government and the electoral calendar

Danish Aid Policy:Theory and Empirical Evidence

This paper is a study of Danish aid policy from the early 1960s to 1995. It includes (i) a review of officially stated aims and criteria, (ii) a descriptive analysis of actual behaviour in international comparative perspective, (iii) a review of the theoretical and empirical aid allocation literature, and (iv) a series of panel data regressions to further explore how Danish bilateral aid was, in actual fact, distributed country-by-country. A theoretical model explaining how the allocation process took place is also formulated. It underpins the empirical analysis from which it transpires that a two step model is a useful way of analysing Danish aid allocations. The first step is whether to select a country or not, and the second involves the decision of how much aid to commit. The empirical analysis demonstrates that Danish aid has been guided in both steps by officially stated aims and criteria in an expected and statistically significant manner although a clear Eastern and Southern Africa bias was found. Another general result is that the relative weights of the explanatory variables have varied both from year-to-year and between sub-periods

Examining the Link between Crime and Unemployment: A Time Series Analysis for Canada

We use national and regional Canadian data to analyse the relationship between economic activity (as reflected by the unemployment rate) and crime rates. Given potential aggregation bias, we disaggregate the crime data and look at the relationship between six different types of crimes rates and unemployment rate; we also disaggregate the data by region. We employ an error correction model in our analysis to test for short-run and long-run dynamics. We find no evidence of long-run relationship between crime and unemployment, when we look at both disaggregation by type of crime and disaggregation by region. Lack of evidence of a long-run relationship indicates we have no evidence of the motivation hypothesis. For selected types of property crimes, we find some evidence of a significant negative short-run relationship between crime and unemployment, lending support to the opportunity hypothesis. Inclusion of control variables in the panel analysis does not alter the findings, qualitatively or quantitatively

New mobilities across the lifecourse: A framework for analysing demographically-linked drivers of migration

Date of acceptance: 17/02/2015Taking the life course as the central concern, the authors set out a conceptual framework and define some key research questions for a programme of research that explores how the linked lives of mobile people are situated in time–space within the economic, social, and cultural structures of contemporary society. Drawing on methodologically innovative techniques, these perspectives can offer new insights into the changing nature and meanings of migration across the life course.Publisher PDFPeer reviewe