Investment decisions in manufacturing: assessing the effects of real oil prices and their uncertainty

We investigate the effects of real oil prices and their uncertainty on investment decisions. Making use of plant‐level data, we estimate dynamic, discrete‐choice models that allow modeling investment inaction, under different assumptions related to initial conditions and unobserved heterogeneity. We find that increases in real oil price changes and in real oil price uncertainty significantly reduce the likelihood of investment action, in line with the predictions of irreversible investment theory. We also document that investment decisions exhibit strong, pure state dependence and are also significantly affected by initial conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

The dynamics of health in the British Household Panel Survey

This paper considers the dynamics of a categorical indicator of self‐assessed health using eight waves (1991–1998) of the British Household Panel Survey (BHPS). Our analysis has three focal points: the relative contributions of state dependence and heterogeneity in explaining the dynamics of health, the existence and consequences of health‐related sample attrition, and the investigation of the effects of measures of socioeconomic status, with a particular focus on educational attainment and income. To investigate these issues we use dynamic panel ordered probit models. There is clear evidence of health‐related attrition in the data but this does not distort the estimates of state dependence and of the socioeconomic gradient in health. The models show strong positive state dependence and heterogeneity accounts for around 30% of the unexplained variation in health. Copyright © 2004 John Wiley & Sons, Ltd.     

Elderly and technology tools: a fuzzyset qualitative comparative analysis

The number of senior citizens is growing globally and governments are striving to find innovative solutions to deal with complex care demands of this part of the population. Technology has been an answer to this situation; however, it is very important that the elderly accept and actually use the technology. This paper empirically tests the senior technology acceptance model using the fsQCA method to analyse data with a sample of 811 seniors aged 60 and over living in Sweden. The results revealed that the necessary conditions for high “perceived ease of use” and “perceived usefulness” are gerontechnology self-efficacy, gerontechnology anxiety, and cognitive abilities; however, each of these is not sufficient on its own. Self-reported health conditions and physical function also play a peripheral role in achieving the desired outcome. Theoretical and managerial implications are discussed at the end of the paper.     

Using dynamic programming with adaptive grid scheme for optimal control problems in economics

The study of the solutions of dynamic models with optimizing agents has often been limited by a lack of available analytical techniques to explicitly find the global solution paths. On the other hand, the application of numerical techniques such as dynamic programming to find the solution in interesting regions of the state was restricted by the use of fixed grid size techniques. Following Grüne (Numer. Math. 75 (3) (1997) 319; University of Bayreuth, submitted, 2003), in this paper an adaptive grid scheme is used for finding the global solutions of discrete time Hamilton–Jacobi–Bellman equations. Local error estimates are established and an adapting iteration for the discretization of the state space is developed. The advantage of the use of adaptive grid scheme is demonstrated by computing the solutions of one- and two-dimensional economic models which exhibit steep curvature, complicated dynamics due to multiple equilibria, thresholds (Skiba sets) separating domains of attraction and periodic solutions. We consider deterministic and stochastic model variants. The studied examples are from economic growth, investment theory, environmental and resource economics.     

Externalities in the matching of workers and firms in Britain

We provide empirical evidence on the nature of spatial externalities in a matching model for Britain. We use a monthly panel of outflows, unemployment and vacancy stocks data from the registers at Jobcentres in Britain; these are mapped onto travel-to-work areas. We find evidence of significant spill-over effects that are generally in line with the predictions of theory. For example, we find that conditional on local labour market conditions, high unemployment levels in neighbouring areas raise the number of local filled vacancies but lower the local outflow from unemployment.     

Inflation aversion in transition countries: Empirical evidence from the Baltic States

In command economies, inflation is either absent or at least unrelated to supply and demand. However, when the economies in Eastern Europe started transforming into market economies, they suddenly experienced high and volatile inflation rates. Transformation countries are therefore interesting laboratories for studying individual inflation aversion. In this paper we study the level and determinants of individual inflation aversion in the three Baltic countries. Using data from 11 waves of the Eurobarometer survey, we find age, education and the macroeconomic situation to have significant effects on the likelihood to mention inflation among the most important problems facing the country. Moreover, we find the populations of all three Baltic countries to be significantly more inflation averse than the population of the United Kingdom, a western democracy with a long tradition as a market economy. We attribute this finding to the specific experiences of the Baltic populations with inflation.     

The impact of bank supervision on loan growth

This paper quantifies the short-term and long-term impact of bank supervision (measured using CAMEL composite and component ratings) on different categories of loan growth: (a) commercial and industrial loans, (b) consumer loans, and (c) real estate loans. For each of these categories, we perform dynamic loan growth equations at the state-level augmented by the inclusion of CAMEL ratings for all banks in the state, after controlling for banking and economic conditions. We perform these regressions for two distinct sub-periods: (1) 1985–1993 (which covers the credit crunch period) and (2) 1994–2004 (which covers the sustained recovery period). For the first period, 1985–1993, we find that out of the three loan categories considered, business lending is the most sensitive to changes in CAMEL ratings (both the composite and the components), although the other loan categories also show some sensitivity. Overall, however, we find little evidence suggesting that the effects of changes in any of the components of CAMEL ratings differ systematically from the effects of changes in the composite CAMEL. For the second period, we find little evidence that changes in CAMEL ratings (the composite or its components) had any systematic effect on loan growth for any of the loan categories considered.     

What do professional forecasters actually predict?

This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component.     

FRED-SD: A real-time database for state-level data with forecasting applications

We construct a real-time dataset (FRED-SD) with vintage data for the U.S. states that can be used to forecast both state-level and national-level variables. Our dataset includes approximately 28 variables per state, including labor-market, production, and housing variables. We conduct two sets of real-time forecasting exercises. The first forecasts state-level labor-market variables using five different models and different levels of industrially disaggregated data. The second forecasts a national-level variable exploiting the cross-section of state data. The state-forecasting experiments suggest that large models with industrially disaggregated data tend to have higher predictive ability for industrially diversified states. For national-level data, we find that forecasting and aggregating state-level data can outperform a random walk but not an autoregression. We compare these real-time data experiments with forecasting experiments using final-vintage data and find very different results. Because these final-vintage results are obtained with revised data that would not have been available at the time the forecasts would have been made, we conclude that the use of real-time data is essential for drawing proper conclusions about state-level forecasting models.     

The location of initial public offering headquarters: An empirical examination

We study the headquarters location of U.S. firms with an initial public offering (IPO) over the 2001–2011 period. Specifically, we examine IPO intensity, defined as IPOs in a state scaled by state population. We find that IPO intensity is positively related to various measures of education. We also find that IPO intensity is positively related to an economic climate (freedom) index, degree of urbanization, and whether a state contains a financial center. Some economists see IPOs as a driver of economic growth. Thus, our results suggest factors that government officials may consider to increase the number of IPOs headquartered in their states.     

MCMC maximum likelihood for latent state models

This paper develops a pure simulation-based approach for computing maximum likelihood estimates in latent state variable models using Markov Chain Monte Carlo methods (MCMC). Our MCMC algorithm simultaneously evaluates and optimizes the likelihood function without resorting to gradient methods. The approach relies on data augmentation, with insights similar to simulated annealing and evolutionary Monte Carlo algorithms. We prove a limit theorem in the degree of data augmentation and use this to provide standard errors and convergence diagnostics. The resulting estimator inherits the sampling asymptotic properties of maximum likelihood. We demonstrate the approach on two latent state models central to financial econometrics: a stochastic volatility and a multivariate jump-diffusion models. We find that convergence to the MLE is fast, requiring only a small degree of augmentation.     

Assessing the impact of crime on the economic performance: the case of central america

Crime is obviously a menace to economic growth and progress, but to acutely understand the enormity of its impact on economic performance for effective policy action, requires a credible means of measurement. Given the crime notoriety of the most of Central America and the struggling state of their economies, this article attempts to discern from econometric evaluation and analyses, the calculable economic impact of crime on the region’s economic progress. From analyses of results, we find the model to be credible and useful following its provision of a much more accurate degree to which crime affects economic performance in Central America, which we find critical to guide policy measures.     

Stochastic interest rates under rational inattention

This paper introduces state uncertainty due to information-processing constraints into the Vasicek model to examine the impacts of rational inattention. By exploiting the term structure of interest rates, we derive closed-form solutions for the subjective bond price and the corresponding bond yield and find that uncertainty induced by informational frictions plays vital roles in undervaluing the bond price and overestimating the bond yield. Furthermore, we clarify the applications of interest rate dynamics under rational inattention and generate the following results: (i) there is an ambiguous relationship between the investor’s channel capacity and option price; (ii) an increase in state uncertainty via a change in the degree of channel capacity is likely to accelerate investment.     

我国水资源区域性短缺和可持续性利用问题分析

我国目前的水资源分布很不均衡,不少地方的水资源极其短缺,严重影响了当地人民的生活和经济发展。而且用水效率也非常低,浪费污染严重。水资源短缺已成为社会经济发展的"瓶颈"。对我国目前的水资源的人口承载力进行估算后,得出的结果是我国目前有14个地区人口超载。然后运用供求、效用和产权等理论,对目前造成水资源短缺的原因进行分析,并提出水资源可持续利用的有效途径。     

Bargaining solutions with non-standard objectives

I examine the pure-strategy solutions of the sealed-bid bargaining game with incomplete information, when the buyer's and seller's objectives are other than the standard objective, namely maximization of expected profit. The motivation for this exploration lies in three problems of the standard formulation: the necessity of assuming common priors, the existence of uncountably many Nash equilibria, with no means for the players to coordinate on any one of them, and the uncertain relationship between these equilibria and observed behavior in bargaining experiments. Specifically, I consider two alternative objectives: minimization of maximum regret, and maximization of maximum profit. The solution concept here is not Nash equilibrium, but rather -individually rational strategy bundle. For that reason, I shall, where appropriate, use the word “solution” in place of “equilibrium.” Yet we find that the notion of Nash Equilibrium reappears, in a sense to be explained. In the minimax-regret case I find (in contrast to the case of expected profit) a unique solution; this solution reduces, for priors with coincident support, to the linear equilibrium of Chatterjee-Samuelson. In the maximum-profit case there are many solutions; they turn out to be slight generalizations of the one-step equilibria of Leininger-Linhart-Radner.     

The long-term labor market consequences of graduating from college in a bad economy

This paper studies the labor market experiences of white-male college graduates as a function of economic conditions at time of college graduation. I use the National Longitudinal Survey of Youth whose respondents graduated from college between 1979 and 1989. I estimate the effects of both national and state economic conditions at time of college graduation on labor market outcomes for the first two decades of a career. Because timing and location of college graduation could potentially be affected by economic conditions, I also instrument for the college unemployment rate using year of birth (state of residence at an early age for the state analysis). I find large, negative wage effects of graduating in a worse economy which persist for the entire period studied. I also find that cohorts who graduate in worse national economies are in lower-level occupations, have slightly higher tenure and higher educational attainment, while labor supply is unaffected. Taken as a whole, the results suggest that the labor market consequences of graduating from college in a bad economy are large, negative and persistent.     

Simulation Estimation of Two‐tiered Dynamic Panel Tobit Models with an Application to the labour Supply of Married Women: A Comment

We find that the empirical results reported in Chang (Journal of Applied Econometrics 2011; 26 (5): 854–871) are contingent on the specification of the model. The use of Heckman's initial conditions combined with observed and not latent lagged dependent variables leads to a counter‐intuitive estimation of the true state dependence. The use of Wooldridge's initial conditions together with the observed lagged dependent variable and a proper modelling of censoring provides a much more natural estimate of the true state dependence parameters together with a clearer interpretation of the decision to participate in the labour market in the two‐tiered model. Copyright © 2015 John Wiley & Sons, Ltd.     

Global Credit Risk: World,Country and Industry Factors

We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high‐dimensional nonlinear non‐Gaussian state‐space model to estimate common components in corporate defaults in a 41 country samples between 1980:Q1 and s2014:Q4, covering both the global financial crisis and euro area sovereign debt crisis. We find that macro and default‐specific world factors are a primary source of default clustering across countries. Defaults cluster more than what shared exposures to macro factors imply, indicating that other factors also play a significant role. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, suggesting that bank credit supply and systematic default risk are inversely related. Copyright © 2016 John Wiley & Sons, Ltd.     

景点规划和保护的可拓方法应用研究

对于旅游城市来说,既要做好规划建设,搭建山水画廊,又要保护重要景点,不失其自然风貌。规划和保护是一对难以协调的矛盾。利用可拓学原理及相关方法在解决矛盾问题方面的优势,通过物元分析和变换模型,将可拓工程方法引入旅游决策,为实现景观设计和景点保护开辟了新的思路。     

Socioeconomic inequality in health-related behaviors: a lifestyle approach

The adoption of certain behaviors—like smoking or physical activity—is recognized as a major factor affecting health. Analyzing the social determinants of these behaviors, then, should be considered an important goal, since it may improve our understanding of the more general phenomenon of health inequalities. In this paper we analyze the association between socioeconomic status (SES) and health-related behaviors among the Italian population aged 18–74 in 2004/2005. Using large-scale sample survey data and a Weberian lifestyle approach, we first identify an ordered multidimensional space of health-related behaviors, and partition this space into a meaningful set of discrete regions representing a fine-grained taxonomy of health lifestyles. Then, we use regression analysis to determine if, and to what extent, the identified lifestyles are associated with SES. Using level of education as an indicator of SES, we find that the propensity to adopt healthier lifestyles exhibits a positive educational gradient, whereas the probability of following less healthy lifestyles is inversely associated with the level of education. We conclude that, in general, focusing on health lifestyles—i.e., on combinations of multiple health-related behaviors—instead of single behaviors may lead to a better understanding of health-related practices and their relationship with socioeconomic status.