Computational suite of models with heterogeneous agents II: Multi-country real business cycle models

This paper describes the second model considered in the computational suite project that compares the performance of different numerical algorithms. It is a multi-country model in which countries face different productivity shocks. Solving such models is a challenging numerical problem unless the number of countries is small. The solutions are functions of a large set of arguments and the functional forms are unknown. Moreover, the solution procedures have to deal with high-dimensional integration problems.     

Forecasting with vector autoregressive (VAR) models subject to business cycle restrictions

In the last decade VAR models have become a widely-used tool for forecasting macroeconomic time series. To improve the out-of-sample forecasting accuracy of these models, Bayesian random-walk prior restrictions are often imposed on VAR model parameters. This paper focuses on whether placing an alternative type of restriction on the parameters of unrestricted VAR models improves the out-of-sample forecasting performance of these models. The type of restriction analyzed here is based on the business cycle characteristics of U.S. macroeconomic data, and in particular, requires that the dynamic behavior of the restricted VAR model mimic the business cycle characteristics of historical data. The question posed in this paper is: would a VAR model, estimated subject to the restriction that the cyclical characteristics of simulated data from the model “match up” with the business cycle characteristics of U.S. data, generate more accurate out-of-sample forecasts than unrestricted or Bayesian VAR models?     

A monetary business cycle model with unemployment

To reproduce key features of the post-war U.S. data, most monetary business cycle models must assume there are high price markups and that agents have high labour supply elasticities despite the existence of contradictory microeconomic evidence. This paper eliminates the need for these assumptions by introducing imperfectly observed effort into a limited participation model. The estimated model is better able to capture the sluggish price response to a monetary policy shock than the standard model, and is consistent with evidence regarding the qualitative responses of the U.S. economy to technology shocks, fiscal policy shocks and monetary policy shocks.     

Income inequality and the business cycle: A threshold cointegration approach

This paper investigates the impact of various socio-economic variables on various cohorts of the income distribution. We use asymmetric cointegration tests to show that unemployment and immigration shocks have real impacts on income inequality. In addition, using threshold test results we are able to show that positive and negative shocks to the economy do not have symmetric effects nor do the impacts of these shocks impact income quintiles uniformly.     

Multi-country real business cycle models: Accuracy tests and test bench

This paper describes the methodology used to compare the results of different solution algorithms for a multi-country real business cycle model. It covers in detail the structure of the model, the choice of values for the parameters, the accuracy tests used in the comparison, and the computer program specifically developed for performing the tests.     

The business cycle model with a unique stable limit cycle

This paper provides the mathematical foundation to the long-standing academic belief that Goodwin's 1951 nonlinear business cycle model has a unique stable limit cycle. In spite of the asymmetric nonlinearity of investment function, the model has certainly a unique stable limit cycle in an economically meaningful region. Once solution paths start from any initial point in the region, they all tend to the limit cycle without escaping from the region or hitting the ceiling or floor of investment during a transition period. The structural stability of the model prevents the limit cycle from vanishing in the face of small perturbations.     

VARs,common factors and the empirical validation of equilibrium business cycle models

Equilibrium business cycle models have typically less shocks than variables. As pointed out by Altug (1989) International Economic Review 30 (4) 889–920 and Sargent (1989) The Journal of Political Economy 97 (2) 251–287, if variables are measured with error, this characteristic implies that the model solution for measured variables has a factor structure. This paper compares estimation performance for the impulse response coefficients based on a VAR approximation to this class of models and an estimation method that explicitly takes into account the restrictions implied by the factor structure. Bias and mean-squared error for both factor- and VAR-based estimates of impulse response functions are quantified using, as data-generating process, a calibrated standard equilibrium business cycle model. We show that, at short horizons, VAR estimates of impulse response functions are less accurate than factor estimates while the two methods perform similarly at medium and long run horizons.     

Some methods for assessing the need for non-linear models in business cycle analysis

It is often suggested that non-linear models are needed to capture business cycle features. In this paper, we subject this view to some critical analysis. We examine two types of non-linear models designed to capture the bounce-back effect in US expansions. This means that these non-linear models produce an improved explanation of the shape of expansions over that provided by linear models. But this is at the expense of making expansions last much longer than they do in reality. Interestingly, the fitted models seem to be influenced by a single point in 1958 when a large negative growth rate in GDP was followed by good positive growth in the next quarter. This seems to have become embedded as a population characteristic and results in overly long and strong expansions. That feature is likely to be a problem for forecasting if another large negative growth rate was observed.     

What do interest rates reveal about the functioning of real business cycle models?

This paper begins by documenting the extent to which the predictions of standard Real Business Cycle (RBC) models are incompatible with observed movements in real interest rates. The main finding of the paper is that extending the baseline model to include habit persistence in consumption and adjustment costs to capital significantly improves the model's empirical performance. In our evaluation of the model's performance, we take special care of estimating and testing predictions of the model using both moments drawn directly from the data and moments calculated after identifying shocks to the stochastic trend.     

A bayesian approach to time-varying cross-sectional regression models

This paper presents a Bayesian approach to regression models with time-varying parameters, or state vector models. Unlike most previous research in this field the model allows for multiple observations for each time period. Bayesian estimators and their properties are developed for the general case where the regression parameters follow an ARMA(s,q) process over time. This methodology is applied to the estimation of time-varying price elasticity for a consumer product, using biweekly sales data for eleven domestic markets. The parameter estimates and forecasting performance of the model are compared with various alternative approaches.     

Integration of family-owned business succession with turnover and life cycle models: Development of a successor retention process model

Family-owned businesses face a unique obstacle: continuation of the business through intergenerational transfer. Most family-owned businesses cease when the next generation does not enter the business. This paper develops parallels between failed intergenerational transfer and voluntary turnover. Based on past research, we develop a taxonomy of characteristics hypothesized to influence intergenerational transfer in family-owned businesses. We, then, integrate these dimensions with prominent turnover and socialization theories to propose a successor retention process model. Implications for research are described.     

A mixed index approach to identifying hedonic price models

Recent literature suggests identifying house price hedonic regressions by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We present an empirical application of a mixed index model, first proposed by Bowden [Bowden, R.J., 1992. Competitive selection and market data: the mixed-index problem. The Review of Economic Studies 59(3):625–633.] to identify hedonic price regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting it more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of lot size and school quality to house price and understates the importance of environmental quality.     

电子商务安全管理的路径探析

文章通过简要分析电子商务安全管理存在的隐患,探讨了防范电子商务安全问题的法律手段、技术手段和监管手段。文章认为,一方面,要不断地完善电子商务的立法和执法,加大电子商务犯罪活动惩治力度;另一方面,在加强电子商务中消费者的权益保障意识的同时,还应从技术手段入手提高电子商务安全管理,构建完善的安全管理体系。如果在电子商务中能够多途径并抓,必定能够达到完善电子商务安全管理的目的。     

A useful tool for forecasting the Euro-area business cycle phases

Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.     

Diffusion of environmental business practices: A network approach

The purpose of this research is to build a conceptual foundation that examines network effects on the diffusion of environmental business practices (EBP) among suppliers. This research extends a network perspective to adoption of an environmental business practice across a large network of suppliers. The context of EBP is used to better understand adoption of a complex business practice, with perceived costs that are often greater than the perceived benefit. Variation in the level of structural and relationship embeddedness affect network diffusion of environmental business practices differently. Increased levels of structural and relational embeddedness are proposed to be positively associated with diffusion of EBP. From a practical standpoint, firms that leverage embeddedness may facilitate higher diffusion and adoption of environmental business practices. This facilitation may lead network actors to engage in EBP, and leverage benefits that may stem from these practices. This research introduces the concept of embeddedness to the environmental supply chain literature. Practicing managers can use the findings in this research to better position themselves within a network to diffuse EBP. This research also helps managers understand how supply chain members that are weakly connected to the primary network are important for introducing new ideas and innovations.     

A two–stage approach to additive time series models

For nonlinear additive time series models, an appealing approach used in the literature to estimate the nonparametric additive components is the projection method. In this paper, it is demonstrated that the projection method might not be efficient in an asymptotic sense. To estimate additive components efficiently, a two–stage approach is proposed together with a local linear fitting and a new bandwidth selector based on the nonparametric version of the Akaike information criterion. It is shown that the two–stage method not only achieves efficiency but also makes bandwidth selection relatively easier. Also, the asymptotic normality of the resulting estimator is established. A small simulation study is carried out to illustrate the proposed methodology and the two–stage approach is applied to a real example from econometrics.     

Tax smoothing in a business cycle model with capital-skill complementarity

This paper undertakes a normative investigation of the quantitative properties of optimal tax smoothing in a business cycle model with state contingent debt, capital-skill complementarity and endogenous skill acquisition under technology and public expenditure shocks. We find that skilled and unskilled labour tax smoothing maintain quantitatively under externalities and exogenous shocks in skill acquisition, as well as when the relative skill supply is exogenously determined. We further find that the government finds it optimal to reduce both the size of the wedge between the marginal rates of substitution and transformation in skill attainment in the long-run and the standard deviation of this wedge over the business cycle. This is achieved by subsidising skill creation and taxing both types of labour income.