Economic and Household Impacts of Projected Policy Changes for the Irish Agri‐food Sector

The policy environment for the Irish agri‐food sector could change rapidly in the coming decade. A potentially positive factor will be the elimination of milk quotas in 2015, although a potentially negative factor will be further trade liberalisation and increased import competition. These changes come on top of the move to decouple direct aids to farmers in 2005 as part of the Mid‐Term Review of the EU's Common Agricultural Policy agreed in 2003. This paper examines these reforms and their impacts on the Irish economy and income distribution using a CGE model particularly rich in detail on the agri‐food sectors, differentiated household groups, and agricultural policy instruments including their links to productive factors and households. The results suggest that the past and projected changes in the policy environment have, in sum, a small positive impact on GDP and household income. However, the gains and losses are unequally distributed across sectors and household groups due to the highly differentiated distribution of support and protection. Although all households generally gain from the sequence of policy reforms in the long run, some experience strong adverse effects from particular reforms and in the medium term.     

Your Governance or Mine?

In response to criticism directed at the resource sector's corporate governance, this paper examines the corporate governance and underlying firm characteristics of resource development stage entities (DSEs) relative to a size‐matched sample of non‐resource firms. We find that resource DSEs have different governance characteristics in the measures of board independence, chair/CEO duality and CEO cash bonuses. Furthermore, there are differences in the information environment measures of analyst following, debt levels, stock market return and stock turnover. Considering we document substantial differences in underlying firm characteristics, corporate governance differences are likely appropriate to the mining industry and should not be uniformly labelled as ‘bad’. Our results suggest that media rankings based on corporate governance scores may not accurately portray the resource sector. Overall, our results are of interest to Australian investors and regulators and contribute to a broader understanding of contextually contingent corporate governance.     

STRATEGIC ASSET ALLOCATION FOR LONG‐TERM INVESTORS: PARAMETER UNCERTAINTY AND PRIOR INFORMATION

We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.     

REPORTING GUIDELINES FOR META-ANALYSIS IN ECONOMICS

Meta-analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta-analyses, the Meta-Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta-analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta-analysis should deviate from them.     

Is real per capita state personal income stationary? New nonlinear,asymmetric panel-data evidence

This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.