An econometric model for ex ante prediction of wildfire suppression costs

This paper develops an econometric model that can provide predictions of fire suppression costs (per acre and in total) for a given large fire before final fire acreage is known. The model jointly estimates cost per acre and acreage equations via Maximum Likelihood, accounting for sample truncation based on final fire size. Formulas and results are shown for predictions of costs and fire size for wildfires in general, and for large fires in particular. Marginal effects of explanatory variables on cost and acreage are discussed. The distribution of these model predictions illustrates the importance of accounting for sample truncation when generating predicted outcomes based on ex ante information.     

REVERSE REGRESSIONS AND LONG‐HORIZON FORECASTING

Long‐horizon predictive regressions in finance pose formidable econometric problems when estimated using available sample sizes. Hodrick in 1992 proposed a remedy that is based on running a reverse regression of short‐horizon returns on the long‐run mean of the predictor. Unfortunately, this only allows the null of no predictability to be tested, and assumes stationary regressors. In this paper, we revisit long‐horizon forecasting from reverse regressions, and argue that reverse regression methods avoid serious size distortions in long‐horizon predictive regressions, even when there is some predictability and/or near unit roots. Meanwhile, the reverse regression methodology has the practical advantage of being easily applicable when there are many predictors. We apply these methods to forecasting excess bond returns using the term structure of forward rates, and find that there is indeed some return forecastability. However, confidence intervals for the coefficients of the predictive regressions are about twice as wide as those obtained with the conventional approach to inference. We also include an application to forecasting excess stock returns. Copyright © 2011 John Wiley & Sons, Ltd.     

Growth Regressions and What the Textbooks Don't Tell You

The paper discusses three econometric problems that are rarely given adequate discussion in textbooks: model uncertainty, parameter heterogeneity, and outliers. Leamer's extreme bounds analysis can be adapted to address all three problems simultaneously. Two examples are presented based on an influential cross-country growth paper by Levine and Renelt ( American Economic Review , vol. 82, 1992, pp. 942-63).     

The network structure of big business in Taiwan

This paper takes a network approach to understanding ownership patterns and director interlocks in Taiwan. In particular, this paper analyzes ties among Taiwan’s top 200 publicly listed companies in 1990 and 2000. The speed of change in Taiwan’s economic organization during the period has been striking. Not only have the identities of many of Taiwan’s largest firms changed, there seems to have been a substantial pruning and thinning of director ties over time and also a substantial transformation of the ownership network. What continuity remains appears to be largely a consequence of business group membership, and the strength of those ties appears to be considerable. Overall, this research finds that Taiwan’s financial sector has been quite central to the island’s big business network, that business groups are an extremely important category for understanding patterns of ownership ties, and that most director interlocks in Taiwan appear to cross industry boundaries rather than occur within them.     

MNEs and development: a review and reconceptualization

In this paper, we review and critique two prominent theories in the international business and international economics literatures regarding the role of multinational enterprises (MNEs) in host country development: the “spillovers” perspective on the impact of MNE investment in host countries and the liabilities of foreignness (LOF) view that specifies the constraints MNEs must overcome to succeed in local, developing country markets. We then propose an alternative conceptualization of MNE-host country relations in which MNEs and local nongovernmental organizations (NGOs) pursue collaborative relationships that make a positive, collective contribution to host country development and to MNE and NGO strategic goals in ways that neither sector is positioned to do alone.     

Who in Brazil Will Gain from Global Trade Reforms?

The potential impacts of multilateral trade liberalisation on developing countries are the subject of numerous controversies. One particular concern is that Brazil, a major agricultural exporter and a country with one of the world's most unequal income distributions, will reap a substantial share of the potential benefits to developing countries from agricultural trade reform, and that most of those benefits will go to large‐scale commercial farmers rather than to the country's smallholders. This claim is explored via a global general equilibrium model and a national model of Brazil containing multiple agricultural and non‐agricultural households. Brazil is found to account for nearly one‐half of all the benefits to developing countries deriving from global agricultural trade reform. These gains are associated with improvements in the welfare of each group and a lower incidence of poverty. Large‐scale producers gain more than smallholders as they tend to be relatively specialised in export products, but there are important gains to agricultural employees, who are relatively poor, and to urban households, who benefit from the expansion of the agro‐food sector. Overall, there is no discernible impact on income inequality, and no evidence that the gains to commercial farmers occur at the expense of poorer households.