A theory of stochastic choice under uncertainty

In this paper we propose a characterization of stochastic choice under risk and under uncertainty. We presume that decision makers’ actual choices are governed by randomly selected states of mind, and study the representation of decision makers’ perceptions of the stochastic process underlying the selection of their state of mind. The connections of this work to the literatures on random choice, choice behavior when preference are incomplete; choice of menus; and grades of indecisiveness are also discussed.     

Quantifying the economic cost of children: a note on intertemporal equivalence scales

Static economic models based on complete demand systems are inadequate for estimating unconditional equivalence scales; in order to capture the effects of demographic changes on consumer behaviour, a life-cycle dynamic model is taken into account. In literature, studies have presented and evaluated longitudinal equivalence scales and intertemporal cost of children but these cannot be applied in practice when equivalence scales are utilised in poverty or income distribution analyses. This paper proposes intratemporal equivalent income scales, which are within period index numbers incorporating intertemporal consumer behaviour.     

Long-term wealth growth portfolio allocation under parameter uncertainty: A non-conservative robust approach

The Kelly portfolio, which is documented to have the highest wealth growth rate of any other portfolio in the long run, has highly risky and unstable performance in the short term. This paper offers a hybrid approach to address this problem by integrating the concept of ridge regression and shrinkage estimation into a robustly modified Kelly portfolio. The proposed approach is a two-stage optimization process that not only takes into account the effect of estimation error but also solves the notoriously conservative problem introduced by the robust optimization method. By extending the worst-case scenarios considered by the robust Kelly portfolio, our approach significantly improves its out-of-sample performance without compromising risk reduction. In an extensive out-of-sample analysis with simulated and empirical data sets, we also characterize the impacts of the robustness level and the length of the rolling window on the final result. Moreover, we conduct a comparative study to confirm the validity of the proposed approach, and our model allows the investor to have a better risk-return trade-off than other traditional models.     

The impact of economic uncertainty on the decision of fertility: Evidence from Taiwan

Economic uncertainty has only recently begun to appear in research on the determinants of fertility. Therefore, the purpose of this study is to investigate how economic uncertainty affects the fertility rate in Taiwan. Official county-level panel data from 1998 to 2016 for 20 counties are utilized in DIFF-GMM and SYS-GMM models in dynamic panel regression estimation. The major finding of this study is that higher volatility of household disposable income will reduce the fertility rate. The empirical results support the proposition that economic uncertainty might be an important determinant of fertility decisions, explaining the decline in fertility in Taiwan.     

Tests for departure from normality in the case of linear stochastic processes

Summary In this paper the asymptotic distributions of the third and the fourth sampling moments of a discrete-parameter linear process are derived together with the asymptotic distributions of the sampling skewness and the excess of kurtosis. The knowledge of these distributions allows us, in the case of “large” samples, to test the departure from normality, a problem which can be regarded as important in various practical applications, but which cannot be treated with the aid of classical tests based on the assumption that the sample values are independent. Some numerical examples illustrate the applications of the proposed tests in practice.

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Zusammenfassung In diesem Beitrage sind die asymptotischen Stichprobenverteilungen der dritten und vierten Momente eines linearen stochastischen Prozesses und auch die asymptotischen Stichprobenverteilungen der Schiefe und des Exzesses der Kurtosis hergeleitet. Die Kenntnis dieser Verteilungen erlaubt für “gro?e” Stichproben die Abweichung der Proze?verteilung von der Normalverteilung zu prüfen, ein Problem, das in vielen F?llen der praktischen Anwendungen wichtig ist, aber mit den klassischen Testen, welche die Unabh?ngigkeit der Stichprobenwerte annehmen, nicht behandelt werden kann. Die praktische Anwendung der vorgelegten Methode ist mit einigen numerischen Beispielen illustriert.

     

经济全球化下人力资源管理发展的新趋势

文章从经济全球化背景入手,对它给企业传统的人力资源管理带来的进行了分析,并对未来人力资源管理发展的新趋势进行了探讨。     

The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress

External financial frictions might increase the severity of economic uncertainty shocks. We analyze the impact of aggregate uncertainty and financial condition shocks using a threshold vector autoregressive (TVAR) model with stochastic volatility during distinct US financial stress regimes. We further examine the international spillover of the US financial shock. Our results show that the peak contraction in euro area industrial production due to uncertainty shocks during a financial crisis is nearly-four times larger than the peak contraction during normal times. The US financial shocks have an influential asymmetric spillover effect on the euro area. Furthermore, the estimates reveal that the European Central Bank (ECB) is more cautious in implementing a monetary policy against uncertainty shocks while adopting hawkish monetary policies against financial shocks. In contrast, the Fed adopts a more hawkish monetary policy during heightened uncertainty, whereas it acts more steadily when financial stress rises in the economy.     

On the convergence of Bayesian posterior processes in linear economic models Counting equations and unknowns

I propose a technique, counting ‘equations’ and ‘unknowns’, for determining when the posterior distributions of the parameters of a linear regression process converge to their true values. This is applied to examples and to the infinite-horizon optimal control of this linear regression process with learning, and in particular to the problem of a monopolist seeking to maximize profits with unknown demand curve. Such a monopolist has a tradeoff between choosing an action to maximize the current-period reward and to maximize the information value of that action. I use the above technique to determine the monopolist's limiting behavior and to determine whether in the limit it learns the true parameter values of the demand curve.     

Consistency and asymptotic normality of maximum likelihood estimation for Gaussian Markov processes from discrete observations

In this paper we prove the weak consistency and the asymptotic normality of the maximum likelihood estimation based on discrete observations ofn independent Gaussian Markov processes. The Ornstein Uhlenbeck process is a special Gaussian Markov process. We derive asymptotic simultaneous confidence regions for the parameters of the Ornstein Uhlenbeck process as an application.     

On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

Analysis of the behavior of technical inefficiency with respect to parameters and variables of a stochastic frontier model is a neglected area of research in frontier literature. An attempt in this direction, however, has recently been made. It has been shown that in a “standard” stochastic frontier model that both the firm level technical inefficiency and the production uncertainty are monotonically decreasing with observational error. In this paper we show, considering a stochastic frontier model whose error components are jointly distributed as truncated bivariate normal, that this property holds if and only if the distribution of observational error is negatively skewed. We also derive a necessary and sufficient condition under which both firm level technical inefficiency and production uncertainty are monotonically increasing with noise-inefficiency correlation. We next propose a new measure of the industry level production uncertainty and establish the necessary and sufficient condition for firm level technical inefficiency and production uncertainty to be monotonically increasing with industry level production uncertainty. We also study the limiting probabilistic behavior of these conditions under different parametric configuration of our model. Finally we carry out Monte Carlo simulations to study the sample behavior of the population monotonic property of the firm level technical inefficiency and production uncertainty in our model.

Dynamic voluntary provision of public goods with uncertainty: a stochastic differential game model

Fershtman and Nitzan (Eur. Econ. Rev. 35:1057–1067, 1991) presented a continuous dynamic public good game and solved the model for feedback Nash equilibria. Wirl (Eur. J. Polit. Econ. 12:555–560, 1996) extended the model and considered nonlinear strategies. Both models do not include uncertainty and hence neglect an important factor in the theory of public goods. We extend the framework of Nitzan and Fershtman and include a diffusion term. We consider two cases. In the first case, the volatility of the diffusion term is dependent on the current level of the public good. This set-up will in principle lead to the same type of feedback strategies computed under certainty. In the second case, the volatility is dependent on the current rate of public good provision by the agents. The results are qualitatively different. We provide a detailed discussion as well as numerical examples. In particular, we show that in both cases uncertainty signifies the free rider effect.     

On the asymptotic behaviour of the Stringer bound1

The Stringer bound is a widely used nonparametric 100(1 -α)% upper confidence bound for the fraction of errors in an accounting population. This bound has been found in practice to be rather conservative, but no rigorous mathematical proof of the correctness of the Stringer bound as an upper confidence bound is known and also no counterexamples are available. In a pioneering paper Bickel (1992) has given some fixed sample support to the bound's conservatism together with an asymptotic expansion in probability of the Stringer bound, which has led to his claim of the asymptotic conservatism of the Stringer bound. In the present paper we obtain expansions of arbitrary order of the coefficients in the Stringer bound. As a consequence we obtain Bickel's asymptotic expansion with probability 1 and we show that the asymptotic conservatism holds for confidence levels 1 -α, with α∈ (0,1/2]. It means that in general also in a finite sampling situation the Stringer bound does not necessarily have the right confidence level. Based on our expansions we propose a modified Stringer bound which has asymptotically precisely the right nominal confidence level. Finally, we discuss other consequences of the expansions of the Stringer bound such as a central limit theorem, a law of the iterated logarithm and the functional versions of them.     

Time-frequency connectedness of crude oil,economic policy uncertainty and Chinese commodity markets: Evidence from rolling window analysis

This article investigates the time–frequency connectedness of economic policy uncertainty (EPU), WTI crude oil and Chinese commodity markets during the period between 2004 and 2020. Rolling window wavelet vector autoregression and connectedness networks are developed to evaluate the time-varying characteristics of the connectedness. The empirical results are as follows: First, the total connectedness between EPU, oil and commodities becomes stronger as the time scale increases. Second, the net connectedness of EPU and WTI in the system is positive, indicating that EPU and WTI are contributors to information and will affect financial markets across time scales. Third, the connectedness remains at a high level during financial crises across all scales, and the contribution of EPU and crude oil to commodities increases significantly. Specifically, compared with other commodity sectors, grains are greatly affected by EPU under the condition that the energy sector is seriously affected by crude oil. Overall, investors and policy makers should consider connectedness in terms of time and frequency when making a decision.     

Location theory of the firm under price uncertainty

This paper presents a theory of location under price uncertainty employing a general utility and production function. The analysis is also conducted by incorporating a homogeneous production function. Risk preferences of the firm are treated as an integral part of the model.     

The economic benefits of market timing the style allocation of characteristic-based portfolios

Many exchange traded funds track simple characteristic-based equity portfolios such as the market capitalization, the fundamental value or the inverse volatility portfolio. This paper provides theoretical and empirical evidence for the economic benefits in exploiting the timing-gains that result from the time-varying relative performance of these characteristic-based portfolios. Under a factor model for expected returns, we show that this dynamic portfolio allocation can be efficient across the low-dimensional set of characteristic-based portfolios. We assess the out-of-sample performance on the S&P 100 universe over the period 1990–2013 and show gains in stability and significant positive risk-adjusted returns for the dynamic style portfolio. We conduct several robustness tests and extensions confirming the benefits of dynamic style allocation across characteristic-based portfolios.     

Location theory of the firm under price uncertainty : Some New Conclusions

This paper presents certain general results of my earlier location theory of the firm under price uncertainty. An expected utility maximizing firm excludes all intermediate locations between the market and raw material site.     

An uncertain suggestion for gold-pricing models: the effect of economic policy uncertainty on gold prices

Gold, whether held in physical form or through financial claims, is of utmost importance to investors, central bankers, and sovereign nations alike. Yet empirically validated explanations of its volatile price remain elusive. Without an ex-post understanding of the determinants of gold prices, ex-ante forecasting is a fruitless endeavor. In this research, an index of US and European economic policy uncertainty is incorporated into a short-run pricing model for gold. The results suggest that in addition to gold being a hedge against inflation, increases in economic policy uncertainty contribute to increases in the price of gold.