Judicial error and cooperation

Cooperation can be induced by an authority with the power to mete out sanctions for free riders, but law enforcement is prone to error. This paper experimentally analyzes preferences for and consequences of errors in formal sanctions against free riders in a public goods game. With type I errors, even full contributors to the public good may be punished. With type II errors, free riders may go unpunished. We find that judicial error undermines cooperation and that the effects of type I and II errors are symmetric. To investigate their relative (dis-)like for error, we let subjects choose what type of error to prevent. We find that subjects prefer type II over type I errors. However, the strength of preferences for preventing type I errors is fully in line with a motive to maximize income and does not indicate any additional psychological or fairness bias against type I errors.     

The limits of self-governance when cooperators get punished: Experimental evidence from urban and rural Russia

We report evidence from public goods experiments with and without punishment which we conducted in Russia with 566 urban and rural participants of young and mature age cohorts. Russia is interesting for studying voluntary cooperation because of its long history of collectivism, and a huge urban–rural gap. In contrast to previous experiments we find no cooperation-enhancing effect of punishment. An important reason is that there is punishment of contributors in all four subject pools. Thus, punishment can also undermine the scope for self-governance in the sense of high levels of voluntary cooperation that are sustained by sanctioning free riders only.     

International aid from the recipient perspective: public or private good input assistance?

This article proposes a theoretical model from the recipient perspective that considers what type of assistance a donor country should provide: public good assistance or private good assistance. We investigate the effects of migration and free riders under both types of assistance. We empirically apply this model to the rapidly growing economies and a large official development assistance disbursement for East Asia.     

Heterogeneous Agents in Public Goods Experiments

We explore by purely experimental means a heterogeneous agents scenario in experimental public goods games, assuming the existence of at least three types of player: free riders, cooperators, and reciprocators. We identify the various types by means of four classification methods, and then play the public goods game with homogeneous groups. We observe that (eq1) the average contribution level is enhanced in this setting; (2) the decay phenomenon is replicated in groups of pure free riders, whereas in groups of cooperative and reciprocating players the contribution is high and fairly stable throughout the game.The experiments reported in this paper were financed by the Cognitive Science Laboratory and the Computational and Experimental Economics Laboratory of the University of Trento. We would like to thank Marco Tecilla, Macrina Marchesin and Dino Parisi for their help in running the experiments, and Luigi Mittone, director of CEEL, for letting us use the laboratorys resources. Paul Webley, Robert Moir, seminar participants at the Universities of Pisa and Trento, Charles Holt and two anonymous referees provided very useful comments on a previous draft.     

Supply‐ versus Demand‐Side Policies in the Presence of Carbon Leakage and the Green Paradox

We consider a climate coalition that seeks to reduce global emissions in the presence of carbon leakage and resource exhaustibility. We show that a credible announcement of future unilateral supply‐side policies delays foreign emissions, and we derive the optimal combination of consumer taxes and producer taxes when we consider leakages from free riders, both within periods and across periods. The tax shares generally differ over time. A decline in the present value of the social cost of carbon over time supports a time path where the consumers’ tax share of the total carbon tax also declines over time. We illustrate our findings with a numerical model.     

Conditional punishment

We elicit human conditional punishment types by conducting experiments. We find that their punishment decisions to an individual are on average significantly positively proportional to other members’ punishment decisions to that individual.     

House price dynamics,conditional higher-order moments,and density forecasts

Most studies on housing price dynamics are only concerned with the conditional mean and variance, but overlook other higher-order conditional moments and the structural change characteristics inherent in housing prices. In order to take into account these two important issues, this study utilizes the generalized Markov switching GARCH model to explore house price dynamics and conditional distribution for US market over 1975Q1–2007Q4. The housing return follows two distinct dynamics: the bust regime and the boom regime. The volatility pattern is different in the bust and boom regimes. In addition, the conditional densities derived by the regime-switching model change dramatically over time and are significantly different from normal distribution. More importantly, the regime-switching model can detect in advance a weak US housing market such as the one that occurred in the middle of 2007. The in-sample fitting ability of regime-switching model, which incorporates higher-order moments, has significant improvements compared to the single-regime AR and AR-GARCH models. For the out-of-sample Value-at-Risk forecasting performance, the ability of regime-switching AR-GARCH model to forecast one-step-ahead density is better compared to the single-regime AR-GARCH model.     

Why do only the G7+2 countries among United Nations members discuss about international public goods? A simulation study

This article investigates why only the Group of 7 plus China and Russia (G7 + 2 countries) among 194 United Nations members discuss about international public goods? By simulating the heterogeneity of income, prices and preference parameters on the total provisions and the number of free riders, we find that the number of contributors for international public goods is 15 under the 194 member countries, while the others are free riders. In addition, the contributors are the top 15 powerful countries with largest dropout value over the world. Then, the discussion with only 15 countries for public goods is meaningful. As large as the heterogeneity of parameters is, the number of contributors becomes closer to G7 + 2.     

A dynamic factor model framework for forecast combination

A panel of ex-ante forecasts of a single time series is modeled as a dynamic factor model, where the conditional expectation is the single unobserved factor. When applied to out-of-sample forecasting, this leads to combination forecasts that are based on methods other than OLS. These methods perform well in a Monte Carlo experiment. These methods are evaluated empirically in a panel of simulated real-time computer-generated univariate forecasts of U.S. macroeconomic time series.     

Hierarchies of ambiguous beliefs

We present a theory of interactive beliefs analogous to Mertens and Zamir [Formulation of Bayesian analysis for games with incomplete information, Int. J. Game Theory 14 (1985) 1-29] and Brandenburger and Dekel [Hierarchies of beliefs and common knowledge, J. Econ. Theory 59 (1993) 189-198] that allows for hierarchies of ambiguity. Each agent is allowed a compact set of beliefs at each level, rather than just a single belief as in the standard model. We propose appropriate definitions of coherency and common knowledge for our types. Common knowledge of coherency closes the model, in the sense that each type homeomorphically encodes a compact set of beliefs over the others’ types. This space universally embeds every implicit type space of ambiguous beliefs in a beliefs-preserving manner. An extension to ambiguous conditional probability systems [P. Battigalli, M. Siniscalchi, Hierarchies of conditional beliefs and interactive epistemology in dynamic games, J. Econ. Theory 88 (1999) 188-230] is presented. The standard universal type space and the universal space of compact continuous possibility structures are epistemically identified as subsets.     

Dynamic modeling under linear-exponential loss

We develop a methodology of parametric modeling of time series dynamics when the underlying loss function is linear-exponential (Linex). We propose to directly model the dynamics of the conditional expectation that determines the optimal predictor. The procedure hinges on the exponential quasi-maximum likelihood interpretation of the Linex loss and nicely fits the multiplicative error modeling framework. Many conclusions relating to estimation, inference and forecasting follow from results already available in the econometric literature. The methodology is illustrated using data on United States GNP growth and Treasury bill returns.     

Punishment and counter-punishment in public good games: Can we really govern ourselves?

A number of experimental studies have shown that the opportunity to punish anti-social behavior increases cooperation levels when agents face a social dilemma. Using a public good experiment, I show that in the presence of counter-punishment opportunities cooperators are less willing to punish free riders. As a result, cooperation breaks down and groups have lower earnings in comparison to a treatment without punishments where free riding is predominant. Approximately one quarter of all punishments are retaliated. Counter-punishments appear to be driven partly by strategic considerations and partly by a desire to reciprocate punishments.     

Household Finances and Social Interaction: Bayesian Analysis of Household Panel Data

We investigate the relationship between social interaction and household finances using the British Household Panel Survey. We explore the relationship between a wide range of aspects of household finances and social interaction, rather than focusing on one particular facet of household finances, such as the holding of stocks and shares. We develop a Bayesian statistical framework to simultaneously explore both sides of the household balance sheet—liabilities and assets. Additionally, we allow the influence of social interaction on household finances to be time dependent, enabling us to model the effects of social interaction from a dynamic perspective. We also develop a two‐part model to jointly investigate the influence of social interaction on the amount of different types of debt and financial assets held conditional on holding the different types of debt and assets. Our analysis suggests that social interaction is associated with households holding larger amounts of debt and assets.     

Volatility spill-overs in commodity spot prices: New empirical results

The classical rational expectations model of commodity markets implies that expected spot price risk is an explanatory variable in spot price regressions; and also that inventory carryover, which is reduced by a larger price variance, creates autoregressive conditional heteroscedastic processes in spot prices. In order to falsify/verify this theory, it has typically been assumed that the square root of the conditional variance of spot prices, a proxy for spot price risk, enters the conditional mean function of spot prices. Based on this simple representation, a typical but counter intuitive outcome has been that spot price risk has an insignificant impact on spot prices, see, e.g., Beck (Beck, S., 1993. A Rational Expectations Model of Time Varying Risk Premia in Commodities Futures Markets: Theory and Evidence. International Economic Review 34, 149–168, Beck, S., 2001. Autoregressive Conditional Heteroskedasticity in Commodity Spot Prices. Journal of Applied Econometrics 16, 115–132). In this paper, we propose an alternative functional relationship (from GARCH(1,1) to GARCH(1,1)-AR(m)) between spot price risk and spot prices that is fully supported by the classical rational expectations model, and based on this new representation we are able to provide stronger empirical support for Muth's rational expectation theory.     

Outline of forecast theory using generalized cost functions

The cost functions used to form forecasts in practice may be quite different than the squared costs that is often assumed in forecast theory. The impact on evaluation procedures is determined and simple properties for the derivate of the cost function of the errors are found to provide simple tests of optimality. For a very limited class of situations are forecasts based on conditional means optimal, generally, the econometricians needs to provide the whole conditional predicted distribution. Implications for multi-step forecasts and the combination of forecasts are briefly considered.     

Elections, exchange rates and reform in Latin America

In this paper, we study the link between real exchange rate (RER) depreciation and elections in Latin America. Our contribution is threefold. First, we employ a statistical model that takes into account the pervasive conditional heteroskedasticity found in financial data and includes a wide range of macroeconomic variables as regressors. Second, we test whether the wave of central bank reform that swept the region has had any effect on the existence or strength of the electoral cycle in exchange rates. Third, we test an additional hypothesis, namely, that financial liberalization may also be an important variable explaining changes in electoral effects on the real exchange rate. In a panel of 9 Latin American countries with available macroeconomic data and a history of exogenous election dates, we confirm the previous findings that real depreciation intensifies after elections even when modeling the significant conditional heteroskedasticity in these data. We also show, for the first time in the literature, that post-election exchange rates are significantly less predictable. We go on to test whether central bank reform has influenced the way in which elections affect the RER in Latin America. If reform has been effective at reducing political manipulation of the exchange rate, then any relationship we see between elections and the RER before central bank reform should be mitigated in the post-reform era. We find that the relationship disappears after reform and that post-reform real exchange rates are also significantly less volatile. Finally, we show that financial liberalization seems to have a stronger effect on the conditional variance of the RER than does central bank reform, but reform has a stronger impact on the conditional mean.     

Can asymmetric conditional volatility imply asymmetric tail dependence?

In this article, we investigate two types of asymmetries, that is, the asymmetry of conditional volatility and the asymmetry of tail dependence in the crude oil markets. We employ the two different sample datasets in which each dataset covers the time period of stable and unstable oil prices, individually. A variety of different copulas and three asymmetric GARCH regression models are used in order to capture the two types of asymmetries. In particular, we extend the TBL-GARCH model proposed by Choi et al. (2012) to the asymmetric GARCH regression type model. The findings from the two different approaches are congruent, in that there is no asymmetry of tail dependence and no asymmetric conditional volatility in crude oil returns over the two different sample periods. Our study reconfirms the findings of Aboura and Wagner (2016) by showing that asymmetric conditional volatility relates to asymmetric tail dependence.     

Viewpoint: An extended class of instrumental variables for the estimation of causal effects

Abstract We examine how structural systems can yield observed variables instrumental in identifying and estimating causal effects. We provide an exhaustive characterization of potentially identifying conditional exogeneity relationships and demonstrate how structural relations determine exogeneity and exclusion restrictions that yield moment conditions supporting identification. This provides a comprehensive framework for constructing instruments and covariates. We introduce notions of conditioning and conditional extended instrumental variables (XIVs). These permit identification but need not be traditional instruments, as they may be endogenous. We distinguish between observed XIVs and proxies for unobserved XIVs. A main message is the importance of sufficiently specifying causal relations governing the unobservables.     

Binary misclassification and identification in regression models

We study a regression model with a binary explanatory variable that is subject to misclassification errors. The regression coefficient is then only partially identified. We derive several results that relate different assumptions about the misclassification probabilities and the conditional variances to the size of the identified set.     

Integrated Risk Management with a Filtered Bootstrap Approach

We present a multi-period risk model to measure portfolio risk that integrates market risk, credit risk and, in a simplified way, liquidity risk. Thus, it overcomes the major limitation currently shared by many risk models that are unable to give a complete picture of all portfolio risks according to a single, coherent framework. The model is based on the Filtered Bootstrap approach; hence, it captures conditional heteroskedasticity, serial correlation and non-normality in the risk factors, that is, most of the features of observed financial time series. Being a simulation risk model, it copes in a natural way with derivatives as it allows the full valuation of the probability density function of the contracts. In addition, it is a suitable and flexible way to generate future scenarios on medium‐term horizons, so this model is particularly appropriate for asset management companies.