International synchronization of the Mexican states business cycles: Explaining factors

The aim of this paper is to identify the explaining factors of the synchronization of the business cycles of the Mexican states and those of the US economy. The cycle indicator is obtained by de-trending the series of total formal employment (Mexican states) and nonfarm employment and industrial production (US). In general, our panel data model estimations suggest the existence of spatial autocorrelation and significant time-period fixed effects. Also, the estimates indicate a significant and positive effect of the ratio of foreign direct investment to gross domestic product (GDP), which may be supplementing the impact of international trade (driven by the most internationally integrated states) and a negative effect of the ratio of remittances to GDP (driven by less integrated states). Finally, the evidence suggests that more similar productive structures yield more synchronized business cycles.     

Do European business cycles look like one?

This paper provides a comprehensive framework to analyze business cycle features other than synchronization. We use stationary bootstrap and model-based clustering methods to analyze similarities and differences among the European cycles. We find evidence that the length, deep and shape of cycles differ across European countries and that these differences are not decreasing over time. Finally, even though we find some correlation between business cycle synchronization and characteristics, there is important information in the characteristics that is not captured by the synchronization measures.     

WILL BUSINESS CYCLES IN THE EURO AREA CONVERGE? A CRITICAL SURVEY OF EMPIRICAL RESEARCH

Abstract.  This survey of business cycle synchronization in the European monetary union focuses on two issues: have business cycles become more similar, and which factors drive business cycle synchronization. We conclude that business cycles in the euro area have gone through periods of both convergence and divergence. Still, there is quite some evidence that during the 1990s business cycle synchronization in the euro area has increased. Higher trade intensity is found to lead to more synchronization, but the point estimates vary widely. The evidence for other factors affecting business cycle synchronization is very mixed.     

Nonlinear effects of government spending shocks in the USA: Evidence from state‐level data

This paper uses state‐level data to estimate the effect of government spending shocks during expansions and recessions. By employing a mixed‐frequency framework, we are able to include a long span of annual state‐level government spending data in our nonlinear quarterly panel VAR model. We find evidence that for the average state the fiscal multiplier is larger during recessions. However, there is substantial heterogeneity across the cross‐section. The degree of nonlinearity in the effect of spending shocks is larger in states that are subject to a higher degree of financial frictions. In contrast, states with a prevalence of manufacturing, mining and agricultural industries tend to have multipliers that are more similar across business cycle phases.     

The impact of the US on Latin American business cycles: A new approach

Business cycles in Latin America have tended to be more volatile than those in wealthier nations such as the US. Accordingly, much research has been conducted on Latin business cycles, as well as the impact of the US on such fluctuations. Some research seeks to find how “integrated” cycles are in the US and Latin America, yielding conflicting results. We apply a new method to the question of business cycle synchronization between the US and nine Latin nations. We find that in the majority of cases integration has been rising in recent years. We also find, contrary to some previous studies, that integration does not appear to be affected by either the level of trade or of capital account openness. Finally, we find that the two countries that are dollarized – Ecuador and El Salvador – appear least integrated with the US. This last finding has potentially troubling implications in terms of the ability of these nations to adjust to asymmetric shocks vis-à-vis the US.     

Inter‐state dynamics of invention activities, 1930–2000

We study the dynamics of the cross‐section distribution of patents per capita for the 48 continental US states from 1930 to 2000 using a discrete‐state Markov chain. We test for and find evidence in favor of the (knowledge) convergence hypothesis. The distribution of patents is converging to a limiting distribution that is significantly more concentrated than its initial distribution. States in the extreme are more mobile than states in the middle of the cross‐sectional distribution and are likely to move to the middle. However, the rate of convergence to the limiting distribution is ‘slow’. Copyright © 2006 John Wiley & Sons, Ltd.     

Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics

We study the dynamic pattern of business cycles using US GDP data between 1790 and 2015. To address difficulties in trend and cycle decomposition, we introduce a semiparametric estimation approach with an iterative plug‐in (IPI) algorithm for endogenous bandwidth selection. This algorithm identifies continuously moving growth trends with trend‐supporting growth periods. A simulation study demonstrates the value‐added of our trend identification. Afterwards, nonlinear SETAR models are fitted parametrically. Further, we test the trend using a recently developed test and the estimated SETAR models against their linear alternatives. The results indicate asymmetric characteristics during booms and busts.     

Macroeconomic Forecasting using Low‐frequency Filters

We consider univariate low‐frequency filters applicable in real‐time as a macroeconomic forecasting method. This amounts to targeting only low frequency fluctuations of the time series of interest. We show through simulations that such approach is warranted and, using US data, we confirm empirically that consistent gains in forecast accuracy can be obtained in comparison with a variety of other methods. There is an inherent arbitrariness in the choice of the cut‐off defining low and high frequencies, which calls for a careful characterization of the implied optimal (for forecasting) degree of smoothing of the key macroeconomic indicators we analyse. We document interesting patterns that emerge: for most variables the optimal choice amounts to disregarding fluctuations well below the standard business cycle cut‐off of 32 quarters while generally increasing with the forecast horizon; for inflation and variables related to housing this cut‐off lies around 32 quarters for all horizons, which is below the optimal level for federal government spending.     

Dichotomous‐choice contingent valuation with ‘dont know’ responses and misreporting

A new approach is presented that simultaneously deals with Misreporting and Don't Know (DK) responses within a dichotomous‐choice contingent valuation framework. Utilising a modification of the standard Bayesian Probit framework, a Gibbs with Metropolis–Hastings algorithm is used to estimate the posterior densities for the parameters of interest. Several model specifications are applied to two contingent valuation datasets: one on wolf management plans, and one on the US Fee Demonstration Program. We find that DKs are more likely to be from people who would be predicted to have positive utility for the bid. Therefore, a DK is more likely to be a YES than a NO. We also find evidence of misreporting, primarily in favour of the NO option. The inclusion of DK responses has an unpredictable impact on willingness‐to‐pay estimates, since it impacts differently on the results for the two datasets we examine. Copyright © 2009 John Wiley & Sons, Ltd.     

Measuring Synchronization and Convergence of Business Cycles for the Euro area,UK and US*

This paper investigates business cycle relations among different economies in the Euro area. Cyclical dynamics are explicitly modelled as part of a time series model. We introduce mechanisms that allow for increasing or diminishing phase shifts and for time‐varying association patterns in different cycles. Standard Kalman filter techniques are used to estimate the parameters simultaneously by maximum likelihood. The empirical illustrations are based on gross domestic product (GDP) series of seven European countries that are compared with the GDP series of the Euro area and that of the US. The original integrated time series are band‐pass filtered. We find that there is an increasing resemblance between the business cycle fluctuations of the European countries analysed and those of the Euro area, although with varying patterns.     

Nonlinear autoregressive leading indicator models of output in G‐7 countries

This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G‐7 countries. Our models use the spread between short‐term and long‐term interest rates as leading indicators for GDP. We examine data admissibility by determining whether these models have the ability to produce time series with classical cycles that resemble the observed classical cycles in the data, and then we ask whether this data admissibility lends itself to better predictions of the probability of recession. Copyright © 2007 John Wiley & Sons, Ltd.     

Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation

Motivated by the need for a positive‐semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra‐high‐frequency asset prices in a state‐space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and expectation maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive‐semidefinite by construction. We show the performance of the KEM estimator using extensive Monte Carlo simulations that mimic the liquidity and market microstructure characteristics of the S&P 500 universe as well as in a high‐dimensional application on US stocks. KEM provides very accurate covariance matrix estimates and significantly outperforms alternative approaches recently introduced in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

A multi‐level panel STAR model for US manufacturing sectors

We introduce a multi‐level smooth transition model for a panel of time series, which can be used to examine the presence of common nonlinear business cycle features across many variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which allows for unrestricted nonlinearity. We introduce a second‐stage model linking the parameters that determine the timing of the switches between business cycle regimes to observable explanatory variables, thereby allowing for lead–lag relationships across panel members. We discuss representation, estimation by concentrated simulated maximum likelihood and inference. We illustrate our model using quarterly industrial production in 19 US manufacturing sectors, and document that there are subtle differences across sectors in leads and lags for switches between business cycle recessions and expansions. Copyright © 2005 John Wiley & Sons, Ltd.     

Real‐Time Nowcasting of GDP: A Factor Model vs. Professional Forecasters

We perform a fully real‐time nowcasting (forecasting) exercise of US GDP growth using Giannone et al.'s (2008) factor model framework. To this end, we have constructed a real‐time database of vintages from 1997 to 2010 for a panel of variables, enabling us to reproduce, for any given day in that range, the exact information that was available to a real‐time forecaster. We track the daily evolution of the model performance along the real‐time data flow and find that the precision of the nowcasts increases with information releases and the model fares well relative to the Survey of Professional Forecasters (SPF).     

The Business School ‘Business’: Some Lessons from the US Experience*

US business schools dominate the business school landscape, particularly for the MBA degree. This fact has caused schools in other countries to imitate the US schools as a model for business education. But US business schools face a number of problems, many of them a result of offering a value proposition that primarily emphasizes the career‐enhancing, salary‐increasing aspects of business education as contrasted with the idea of organizational management as a profession to be pursued out of a sense of intrinsic interest or even service. We document some of the problems confronting US business schools and show how many of these arise from a combination of a market‐like orientation to education coupled with an absence of a professional ethos. In this tale, there are some lessons for educational organizations both in the US and elsewhere that are interested in learning from the US experience.     

Globalization vs. Europeanization: A Business Cycles Race*

This paper examines the relative cyclical affiliation in six industrialized economies. While the broad conclusions are consistent with the existing literature, the proposed empirical framework is not based on correlations and permits the analysis of relative groupwise synchronization under very few assumptions. The results allow us to conclude that an English‐speaking club (Canada, UK, USA) is emerging in the last decades, whereas explicit and formal commitments seem to have had a relatively weaker power in determining Euro‐zone (France, Germany, Italy) business cycle comovements. Altogether, the business cycle race is a cause for concern as regards the entry of the UK into the Euro‐zone.     

National influences on European Works Councils in UK‐ and US‐based companies

The view that the role of European Works Councils (EWCs) is shaped predominantly by national industrial relations (IR) traditions in the company's country of origin derives largely from the experience of EWCs in companies based in continental Europe. This article argues that a more differentiated approach to the influence of national IR factors on EWCs needs to be developed to take account of the circumstances of companies headquartered in the UK and the US, whose national IR arrangements do not provide a strong institutional model for the EWC and, in the case of US‐based companies, where headquarters management has little or no direct involvement in the EWC. Findings from comparative case studies of EWCs in eight UK‐ and US‐based multinationals suggest that their character is shaped by the interplay between ‘country‐of‐origin’ factors,‘country‐of‐location’ factors and structural, company‐specific considerations.     

The EC‐LQO five‐factor framework: An alternative lens for business model innovation in highly knowledge‐intensive industries

Growing technological complexity continues to drive firms to interact with the external innovation environment to achieve firm success. However, industries' complexities and the business model concept's underlying ontology have limited research on modeling the key factors that enable this interface. In this study, results of an empirical analysis of a unique dataset of 102 biopharmaceutical companies broadly support the EC‐LQO five‐factor framework as a useful tool to guide business model innovation for highly knowledge‐intensive environments.     

Duration dependence in US business cycles: An analysis using the modulated power law process

The modulated power law process is used to analyze the duration dependence in US business cycles. The model makes less restricting assumptions than traditional models do and measures both the local and global performance of business cycles. The results indicate evidence of positive duration dependence in the U.S. business cycles. Structural change after WWII in both expansion and contraction phases of business cycles is also documented. Hypothesis tests confirm that the model fits US business cycles.      

Strategic inter‐organizational environmentalism in the US: A multi‐sectoral perspective of alternating eco‐policy roles

During the last several decades, numerous policies and programs intended to advance environmental goals have been formulated in the US by governmental bodies and implemented by businesses and nongovernmental organizations. This article forwards a multi‐sectoral perspective that business and nonprofit organizations have also been significantly involved in environmental policy and program formulation, as well as implementation, and that governments have also fulfilled the latter strategic role in US environmental policy. In this article, nine US environmental initiatives are described and categorized according to which of the three sectors' organizations were significant formulators of the programs and which were significant implementors. Implications for future research include investigation of other environmental dyadic program combinations in addition to those presented, extension of the present analysis beyond dyads into environmental policy networks, inclusion of the strategic environmental program evaluation stage to complement formulation and implementation and exploration of effectiveness variables in cross‐sectoral, inter‐organizational collaborations. Implications for educators and practitioners are also presented. Copyright © 2002 John Wiley & Sons, Ltd. and ERP Environment.