Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes

This article provides out-of-sample forecasts of Nevada gross gaming revenue (GGR) and taxable sales using a battery of linear and non-linear forecasting models and univariate and multivariate techniques. The linear models include vector autoregressive and vector error-correction models with and without Bayesian priors. The non-linear models include non-parametric and semi-parametric models, smooth transition autoregressive models, and artificial neural network autoregressive models. In addition to GGR and taxable sales, we employ recently constructed coincident and leading employment indexes for Nevada’s economy. We conclude that the non-linear models generally outperform linear models in forecasting future movements in GGR and taxable sales.     

航空公司不同商业模式的均衡分析

文章首先对航空公司商业模式进行了划分;其次,通过微观经济模型,分别分析了几种典型商业模式的均衡条件;最后,讨论了航空公司不同商业模式均衡对完善国家航线结构和明确民用机场定位所具有的意义。     

LIVING RATIONALLY UNDER THE VOLCANO? AN EMPIRICAL ANALYSIS OF HEAVY DRINKING AND SMOKING*

This study investigates whether models of forward‐looking behavior explain the observed patterns of heavy drinking and smoking of men in late middle age in the Health and Retirement Study better than myopic models. We develop and estimate a sequence of nested models that differ by their degree of forward‐looking behavior. Our empirical findings suggest that forward looking models fit the data better than myopic models. These models also dominate other behavioral models based on out‐of‐sample predictions using data of men aged 70 and over. Myopic models predict rates of smoking for old individuals, which are significantly larger than those found in the data on elderly men.     

城市空间增长模型研究的趋势、类型与方法

城市空间分散化增长蔓延的趋势要求对未来城市空间的发展方向进行预测研究。文章在对城市空间模型的研究案例及发展趋势进行总结的基础上,将城市空间模型总结为四种类型,分别是基于因果关系的城市空间增长影响因素静态模型、基于空间发展理论和GIS空间分析的准动态城市空间增长模型、基于系统动力学微分方程(组)的城市空间增长动态模型、以及基于微观主体作用演变机制的城市空间增长模拟模型,并认为城市空间增长模型将向微观离散化发展。     

IMPORT FORECASTS FOR INPUT-OUTPUT MODELS*

The paper presents forecasting models for (1) the share of competitive imports in the total demand for a commodity group and (2) the level of demand for competitive imports of a commodity group. The two forecasting models are used, respectively, with (1) input-output models which incorporate market share parameters as one vector of coefficients and (2) input-output models which assume imports have been determined autonomously. It is shown that these two types of input-output models can be made workable by prefixing one or other of the import forecasting models to the input-output model. Tests are made of the forecasting ability of the combined models.     

Modeling household fertility decisions: estimation and testing of censored regression models for count data

"This paper adds to the recent body of research on fertility by estimating and testing censored Poisson regression models and censored negative binomial regression models of household fertility decisions. A novel feature of this study is that in each case the censoring threshold varies from individual to individual. Also, a Lagrange multiplier or score test is used to investigate overdispersion. In these regression models the dependent variable is the number of children. In this situation, censored Poisson regression models and censored negative binomial regression models have statistical advantages over OLS, uncensored Poisson regression models, and uncensored negative binomial regression models. The censored models employed in this study are estimated using panel data collected from the Consumer Expenditure Survey compiled by the [U.S.] Bureau of Labor Statistics."     

Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models

The promotion of energy-efficient appliances is necessary to reduce the energetic and environmental burden of the household sector. However, many studies have reported that a typical consumer underestimates the benefits of energy-saving investment on the purchase of household electric appliances. To analyze this energy-efficiency-gap problem, many scholars have estimated implicit discount rates that consumers use for energy-consuming durables. Although both hedonic and choice models have been used in previous studies, a comparison between the two models has not yet been made. This study uses point-of-sale data about Japanese residential air conditioners and estimates implicit discount rates with both hedonic and choice models. Both models demonstrate that a typical consumer underinvests in energy efficiency. Although choice models generally estimate a lower implicit discount rate than hedonic models, the latter models estimate the values of other product characteristics more consistently than choice models.     

First-purchase diffusion models of new-product acceptance

This article constitutes a review and exposition of first-purchase diffusion models of new-product acceptance. These models have been developed to predict the cumulative number of new-product adopters over time and serve the purpose of forecasting sales for durable goods and novelty items. In addition to considering traditional models, a number of recent models are reviewed and illustrated, and limitations and further extensions of the models are discussed.     

Positive public economics: reinterpreting ‘optimal’ policies

The standard positive/normative divide fails to capture the way economists use ‘optimal’ taxation models. This paper argues that the better way to understand public economics is through a three-part division between positive, normative, and instrumental models. An instrumental model is about means and ends. Once this additional dimension is acknowledged, one can see that ‘optimal’ taxation models are closely connected to what are generally seen as purely positive models. I argue that economists have been using similar standards to assess ‘optimal’ taxation models as they use to assess positive models. Recent advances in optimal taxation theory have embraced the positive aspects of models, even about social welfare functions, something that is generally classified as a normative.     

Differences and similarities between ecological and economic models for biodiversity conservation

In this paper we investigate an important obstacle which substantially complicates co-operation between ecologists and economists but which has received little attention so far: differences between the modelling approaches in economics and ecology. To understand these differences, 60 models addressing issues relevant to biodiversity conservation have been selected randomly from eight international economic and ecological journals. The models have been compared according to a number of criteria including the models' level of generality; the mathematical techniques employed for formulation and solution of the models; the level of complexity and the way time, space and uncertainty are taken into account. The economic models sampled are formulated and analysed analytically, tend to be relatively simple and are mostly used to investigate general questions. Furthermore, they often ignore space, dynamics and uncertainty. Although some ecological models have similar properties, there is also a substantial number of another type of ecological models that are relatively complex and analysed by simulation. These models tend to be rather specific and often explicitly consider dynamics, space and uncertainty. The integrated ecological-economic models are observed to lie “in the middle” between ecological and economic models. An unexpected result is that they are not more complex than ecological and economic models (as one could have expected from a simple “merger” of models from both disciplines), but have an intermediate complexity.     

Limits and possibilities of large-scale long-range societal models

It is argued that the appropriate criteria for evaluating large-scale long-range societal (or “world”) models differ significantly from the criteria that are appropriate for short-range econometric models or for small “toy” models. World models are designed to elucidate major societal problems arising from the interaction of many loosely connected factors—demographic, economic, technological, and environmental—that can be safely neglected in short-range extrapolative models. World models are also intended to explore the implications of long-range policy alternatives. Consequently, it is important that world models be phenomenological, rather than statistical, and they must “capture” the essence of some inherently nonlinear phenomena. This implies achieving qualitative realism without imposing an unwarranted assumption of causal determinism. Unfortunately, the mathematical characteristics of large nonlinear systems may essentially preclude meaningful long-run forecasts.     

Short-term inflation forecasting models for Turkey and a forecast combination analysis

In this paper, we produce short term forecasts for the inflation in Turkey, using a large number of econometric models. In particular, we employ univariate models, decomposition based approaches (both in frequency and time domain), a Phillips curve motivated time varying parameter model, a suite of VAR and Bayesian VAR models and dynamic factor models. Our findings suggest that the models which incorporate more economic information outperform the benchmark random walk, and the relative performance of forecasts are on average 30% better for the first two quarters ahead. We further combine our forecasts by means of several weighting schemes. Results reveal that, the forecast combination leads to a reduction in forecast error compared to most of the models, although some of the individual models perform alike in certain horizons.     

Technological innovation and complexity theory

Complexity theory has become influential in recent models in social science. In the context of innovations and new technologies, most applications have focused on technology adoption and technology diffusion, whereas the topic of the innovation process has received less attention. This paper discusses three families of complexity models of technological innovation: fitness landscape models, network models and percolation models. The models are capable of analysing complex interaction structures (between components of technologies, between agents engaged in collective invention) while avoiding ‘over-parameterisation’. The paper ends with discussing the methodological challenges and critiques regarding the application of complexity theory that remain.     

铁路成本代理模型研究

讨论了建立铁路成本代理模型的主要背景、设计思路、模型结构框架、主要内容、基本原理和实现的主要方法,以及模型的维护等问题。铁路成本代理模型主要作用在于运用工程分析的基本原理和方法,借助于财务会计核算数据,通过优化和控制策略的选择,科学准确地体现铁路运输生产活动的整体运输网络的联动特征,进而确定不同优化目标下的最优结果。     

Multicrop Production Models with Multinomial Logit Acreage Shares

The main objective of this paper is to show that the MultiNomial Logit (MNL) framework can be used for deriving simple acreage share models. More specifically we show that MNL acreage choice models can be defined as parts of consistent multicrop models. When coupled with suitably designed crop production models, e.g. a specific parameterization of the standard quadratic yield function, the parameters of these multicrop models are easily interpreted and estimated. Although MNL acreage choice models are usually derived by aggregating crop choices defined at the plot level, we show that these models can also be derived by considering a profit maximisation problem at the farm level. This provides a simple theoretical background for the Standard MNL acreage share model, as well as for simple extensions of these models: the Nested MNL acreage share models. An empirical application on French farm-level data over the period 1996–2007 investigates the empirical performances of the multicrop econometric models based on the proposed MNL framework for modelling acreage choices.     

Which is the best: A comparison of asset pricing factor models in Chinese mutual fund industry

Factor models are commonly used in estimating risk-adjusted fund performance. We compare the commonly used factor models in empirical asset pricing studies and find that Fama and French (2015) five-factor model outperforms other models in the Chinese mutual fund industry and in most fund segments. The factor models we tested are more effective in explaining the return of index funds than other types. Meanwhile, we also find that the capital asset pricing model (CAPM) better controls the estimated alpha dispersion than other models. Though most multifactor models including Carhart (1997) have higher R-squared than CAPM, the cross-sectional differences between them are not statistically significant.     

Modelling conditional heteroskedasticity: Application to the “IBEX-35” stock-return index

This paper compares alternative time-varying volatility models for daily stock-returns using data from Spanish equity index IBEX-35. Specifically, we estimate a parametric family of models of generalized autoregressive heteroskedasticity (which nests the most popular symmetric and asymmetric GARCH models), a semiparametric GARCH model, the generalized quadratic ARCH model, the stochastic volatility model, the Poisson Jump Diffusion model and, finally, a nonparametric model. Those models which use conditional standard deviation (specifically, TGARCH and AGARCH models) produce better fits than all other GARCH models. We also compare the within sample predictive power of all models using a standard efficiency test. Our results show that the asymmetric behaviour of responses is a statistically significant characteristic of these data. Moreover, we observe that specifications with a distribution which allows for fatter tails than a normal distribution do not necessarily outperform specifications with a normal distribution.     

我国国有企业治理模式的优化选择

本文从公司治理的基本模式出发，分析不同公司治理模式的理论前提、社会背景和基本特征；并通过对公司治理模式的再梳理，指出企业资本结构是影响公司治理模式选择的内生因素；进而从公司治理的本质入手，构建了一个一般性的模型．分析公司治理模式分化的原因以及选择的依据；最后，对我国国有企业公司治理模式的选择提出了一些建议。