Military spending and economic growth in China: a regime-switching analysis

This article has been made available through the Brunel Open Access Publishing Fund.This article investigates the impact of military spending changes on economic growth in China over the period 1953 to 2010. Using two-state Markov-switching specifications, the results suggest that the relationship between military spending changes and economic growth is state dependent. Specifically, the results show that military spending changes affect the economic growth negatively during a slower growth-higher variance state, while positively within a faster growth-lower variance one. It is also demonstrated that military spending changes contain information about the growth transition probabilities. As a policy tool, the results indicate that increases in military spending can be detrimental to growth during slower growth-higher growth volatility periods. © 2014 © 2014 The Author(s). Published by Taylor & Francis

An empirical characterization of mortgage default in Colombia between 1997 and 2004

This paper examines the relationship between mortgage default decisions and relevant observable variables under the light of a random utility model. The focus of the study is the Colombian mortgage market between 1997 and 2004 using two separate data sets that are matched using simulation techniques. The estimation allows the computation of mortgage default probabilities that are directly related to an underlying model of optimal default. Results are sharp and indicate that variation in current income has little effect on mortgage default, compared to housing prices and mortgage balances.D4; G21; L13; R12 Classification JEL: Banking; Location; Competition; Colombia.

Modeling Heteroskedasticity of Crop Yield Distributions: Implications for Normality

The paper analyzes the extent to which ignorance of heteroskedasticity or its inadequate modeling would result in misleading statistical inferences about crop yield distribution. We follow the "detrending mean yield approach" in which we model the conditional mean yield using a panel data model. We assume alternative structures of variance-covariance matrix for the random component. Heteroskedasticity robust and non-robust estimation methods are used before performing a joint normality test on the random component of crop yield data. Our findings provide evidence against the claim that virtually all previous findings of non-normality in crop yields are infected because of the ignorance of heteroskedasticity or its inappropriate modeling. Accounting for heteroskedasticity in crop yield data would matter for validity of evidence against normality only to the extent that its proportion among the source of departure from normal distribution is relatively sizable.Research Methods/ Statistical Methods,

A Small-Sample Study of the New-Keynesian Macro Model

This paper presents a small-sample study of the threeequation- three variable New-Keynesian macro model. While the point estimates imply that the Fed has been stabilizing inflation fluctuations since 1980, our econometric analysis suggests considerable uncertainty regarding the stance of the Fed against inflation. We show that, if we add first order autocorrelation to the error terms of the New- Keynesian model, this is only marginally rejected.

Asset Returns and State-Dependent Risk Preferences

We propose a consumption-based capital asset pricing model in which the representative agent's preferences display state-dependent risk aversion. We obtain a valuation equation in which the vector of excess returns on equity includes both consumption risk as well as the risk associated with variations in preferences. We develop a simple model that can be estimated without specifying the functional form linking risk aversion with state variables. Our estimates are based on Markov chain Monte Carlo estimation of exact discrete-time parameterizations for linear diffusion processes. Since consumption risk is not forced to account for the entire risk premium, our results contrast sharply with estimates from models in which risk aversion is state-independent. We find that relaxing fixed risk preferences yields estimates for relative risk aversion that are (i) reasonable by usual standards, (ii) correlated with both consumption and returns and (iii) indicative of an additional preference risk of holding the assets. Nous suggérons un modèle d'équilibre de prix des actifs où les préférences de l'agent représentatif sont caractérisées par une aversion contingente au risque. Nous obtenons une équation de valorisation où la prime de risque dépend du risque de préférences en plus du risque de consommation habituel. Nous développons une application empirique qui ne nécessite pas une forme fonctionnelle reliant l'aversion non-observable à des variables économiques observables. Nos estimations sont basées sur une estimation en chaîne markovienne de Monte-Carlo pour des vraisemblances exactes de processus linéaires de diffusion appliquées aux données en temps discret. Puisque le risque de consommation n'a plus à justifier seul la forte prime de risque observée sur les fonds propres, nos estimations contrastent fortement avec celles obtenues dans le cas standard où l'aversion au risque est constante. En particulier, nous trouvons des estimés de l'aversion au risque qui sont (i) de niveau raisonnable, (ii) corrélés avec la consommation et les rendements et (iii) cohérents avec un risque additionnel de détention d'actifs.Asset Pricing Models, Bayesian Analysis, Continuous-time Econometric Models, Data Augmentation, Equity Premium Puzzle, Markov Chain Monte Carlo, Risk Aversion, State-Dependent Preferences, Wealth, Modèles de prix des actifs, analyse bayesienne, modèles économétriques en temps continu, augmentation de données, énigme de la prime de risque, chaîne markovienne de Monte Carlo, aversion au risque, préférences contingentes, richesse

Pre-harvest Forecasting of County Wheat Yield and Wheat Quality Conditional on Weather Information

Wheat regression models that account for the effect of weather are developed to forecast wheat yield and quality. Spatial lag effects are included. Wheat yield, protein, and test weight level are strongly influenced by weather variables. The forecasting power of the yield and protein models was enhanced by adding the spatial lag effect. Out of sample forecasting tests confirm the models’ usefulness in accounting for the variations in average wheat yield and qualities.prediction, protein, spatial lag, test weight, weather, wheat yield, Agribusiness, Environmental Economics and Policy, Farm Management, Production Economics, Productivity Analysis, Risk and Uncertainty,

Asset Returns and State-Dependent Risk Preferences

We propose a consumption-based capital asset pricing model in which the representative agent's preferences display state-dependent risk aversion. We obtain a valuation equation in which the vector of excess on equity includes both consumption risk as well as the risk associated with variations in preferences. We develop a simple model that can be estimated without specifying the functional form linking risk aversion with state variables. Our estimates are based on Markov chain Monte Carlo estimation of exact discrete-time parameterizations for linear diffusion processes. Since consumption risk is not forced to account for the entire risk premium, our results contrast sharply with estimates from models in which risk aversion is state-independent. We find that relaxing fixed risk preferences yields estimates for relative risk aversion that are (i) reasonable by usual standards, (ii) correlated with both consumption and returns and (iii) indicative of an additional preference risk of holding the asests.Asset pricing models, Bayesian analysis, continuous-time econometric models, data augmentation, equity premium puzzle, Markov chain Monte Carlo, risk aversion, state-dependent preferences, wealth

The Selectivity of Fertility and the Determinants of Human Capital Investments: Parametric and Semi-Parametric Estimates

In this paper we assess the importance of heterogeneity and selective fertility in altering estimates and interpretations of the determinants of the human capital of children. We set out a sequential model of human capital investments in children incorporating endogenous fertility and heterogeneity in human capital endowments to illustrate the fertility selection problem and issues of identification. Empirical results based on parametric and semi-parametric estimates of selectivity models applied to data on birthweight and schooling in Malaysia indicate that the hypothesis of no fertility selection is strongly rejected, with mothers having higher birthweight children tending to have substantially lower birth probabilities (negative birth selectivity). As a consequence, the positive association between mother's schooling and birthweight is substantially underestimated and the positive effects of delaying childbearing overestimated when birth selectivity is not taken into account. The schooling results indicate strong rejection of the "efficient schooling" model, in which schooling is allocated efficiently across children, but only when the selectivity of fertility is taken into account.Labor and Human Capital,