Testing the Technology of Human Capital Production: A General‐to‐Restricted Framework

Studies of childhood development have suggested human capital is accumulated in complex and nonlinear ways. Nonetheless, empirical analyses of this process often impose a linear functional form. This paper investigates which technology assumptions matter in quantitative models of human capital production. I propose a general‐to‐restricted procedure to test the production technology, placing constraints on a modified McCarthy function, from which transcendental, constant elasticity of substitution, log‐linear and linear models are obtained as special cases. Applying the procedure to data on child height from the Young Lives surveys, as well as cognitive skills, I find that the technology of human capital production is neither log‐linear nor linear‐in‐parameters; rather, past and present inputs act as complements. I recommend that maintained hypotheses underlying functional form choices should be tested on a routine basis.     

NON‐LINEAR DYNAMICS,COMPLEXITY AND RANDOMNESS: ALGORITHMIC FOUNDATIONS

Abstract In this paper I make an attempt to describe, discuss and extend a few aspects of the rich mathematical tapestry that can be woven with rigorous notions of non‐linear dynamics, complexity and randomness, in terms of algorithmic mathematics. It is a tapestry that I try to weave with economic analysis, economic theory and economic modelling in mind. All three notions – that is, non‐linear dynamics, complexity and randomness – have a rich conceptual, modelling or analytic tradition in core areas of economic theory, both at the micro and macro levels. It is the algorithmic foundation I try to provide for them that could be considered the novel contribution in this paper. Once the algorithmic foundations are in place, it is, for example, almost natural to consider the famed difficulties of obtaining closed form solutions for non‐linear, complex or random dynamic models in economics almost a trivial vestige of a pre‐simulation era in mathematical modelling.     

Semi‐parametric estimation of consumption‐based equivalence scales: the case of Germany

Consumption‐based equivalence scales are estimated by applying the extended partially linear model (EPLM) to the 1998 German Income and Consumption Survey (EVS). In this model the equivalence scales are identified from nonlinearities in household demand. The econometric framework should not therefore impose strong restrictions on the functional forms of household expenditure shares. The chosen semi‐parametric specification meets this requirement. It is flexible, it yields ‐consistent parameter estimates and it is consistent with consumer theory. Estimated equivalence scales are below or in the range of the expert equivalence scales of the German social benefits system. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation and inference under economic restrictions

Estimation of economic relationships often requires imposition of constraints such as positivity or monotonicity on each observation. Methods to impose such constraints, however, vary depending upon the estimation technique employed. We describe a general methodology to impose (observation-specific) constraints for the class of linear regression estimators using a method known as constraint weighted bootstrapping. While this method has received attention in the nonparametric regression literature, we show how it can be applied for both parametric and nonparametric estimators. A benefit of this method is that imposing numerous constraints simultaneously can be performed seamlessly. We apply this method to Norwegian dairy farm data to estimate both unconstrained and constrained parametric and nonparametric models.     

Board Antecedents of CEO Duality and the Moderating Role of Country‐level Managerial Discretion: A Meta‐analytic Investigation

CEO duality reduces boards’ monitoring capacity. But governance substitution theory holds that boards of directors who can effectively monitor their CEOs are more likely to adopt the CEO duality governance structure. By examining relationships between board characteristics underlying their monitoring capacity and CEO duality, we bring evidence to bear on governance substitution theory. Further, by applying a managerial discretion theory lens to CEO duality, we extend governance substitution theory to the cross‐country context where institutional features vary in their constraints on managerial discretion. Meta‐analytic results from a dataset of 297 studies across 32 countries/regions provided support for the majority of our predictions. As predicted, board independence and certain types of board human capital were positively related to CEO duality. Unexpectedly, board ownership was negatively related to CEO duality. Additionally, country‐level managerial discretion significantly moderated the board independence‐ and human capital‐duality relationships (but not the board‐ownership‐duality relationship) as predicted.     

Statistical Approaches for Non‐parametric Frontier Models: A Guided Tour

A rich theory of production and analysis of productive efficiency has developed since the pioneering work by Tjalling C. Koopmans and Gerard Debreu. Michael J. Farrell published the first empirical study, and it appeared in a statistical journal (Journal of the Royal Statistical Society), even though the article provided no statistical theory. The literature in econometrics, management sciences, operations research and mathematical statistics has since been enriched by hundreds of papers trying to develop or implement new tools for analysing productivity and efficiency of firms. Both parametric and non‐parametric approaches have been proposed. The mathematical challenge is to derive estimators of production, cost, revenue or profit frontiers, which represent, in the case of production frontiers, the optimal loci of combinations of inputs (like labour, energy and capital) and outputs (the products or services produced by the firms). Optimality is defined in terms of various economic considerations. Then the efficiency of a particular unit is measured by its distance to the estimated frontier. The statistical problem can be viewed as the problem of estimating the support of a multivariate random variable, subject to some shape constraints, in multiple dimensions. These techniques are applied in thousands of papers in the economic and business literature. This ‘guided tour’ reviews the development of various non‐parametric approaches since the early work of Farrell. Remaining challenges and open issues in this challenging arena are also described. © 2014 The Authors. International Statistical Review © 2014 International Statistical Institute     

Hard and Soft Densification Policies in the Paris City‐Region

This essay is concerned with the planning and densification of suburbs, which present a huge challenge insofar as they form a large area of urbanized land that remains underexploited due to low residential density. Drawing on current research in the Paris city‐region, the essay focuses specifically on the difficulty in implementing densification policies in low‐rise suburban areas. It examines the varying degrees of densification fostered by these policies, and builds upon recent urban studies literature on suburban change to trace how suburban areas are being transformed through regulations, instruments and market dynamics associated with densification processes. What kinds of densification policy are being implemented and what are the socio‐economic, political and cultural determinants of each type of regulatory approach? This essay will attempt to answer this question via an analysis of the densification policies being put in place in the municipalities of the Paris city‐region. It will offer in turn a typology of these different policies. It shows that densification is an instrument that can be used to address local political concerns which vary greatly depending on the economic, social and geographical position of municipalities within larger urban areas.     

Co‐evolution in an Institutionalized Environment*

abstract This paper examines the extent to which co‐evolution can take place within a heavily constrained environment and how changes in the degree of institutionalization are relevant to opportunities for exercising strategic choice at the level of the firm. It addresses these questions through a detailed case study of a major Brazilian telecommunications company, Telemig, covering its life span of 27 years from 1973 to 2000. The insights obtained advance the theory of co‐evolution by incorporating a political dimension of how organizations are transformed into new forms. In the case studied, new forms arose with radical changes in the rules affecting competition and with de‐institutionalization of the economic regime by coalitions of actors who were strategically located in networks that crossed system levels. Although the Telemig case presents circumstances different to those usually addressed by studies of co‐evolution, it nevertheless points to the virtues of combining a strategic choice approach with one that focuses on the isomorphic effects of institutional constraints.     

Aqui No Se Habla Agencia.* An Examination of the Impact of Adverse Selection and Framing in Decision‐Making: a US/Mexico Comparison

US companies seeking cheaper labor or extraordinary returns have often seen foreign direct investment as a panacea. However, many of these companies founder on the horns of a control dilemma. While raw economic data such as labor rates prove to be true, productivity and decision‐making styles are so different that companies fail to maximize their investment returns. This situation is worsened as companies attempt to impose culturally inappropriate home country controls on their foreign investment. This study examines one of the potential sources of failure, escalation of commitment, which occurs when decision‐makers over‐commit incremental resources to failing investments without reasonable probability of recovery. This behavior has been widely documented in US domestic literature (see Whyte and Hook, 1997 , for a summary). However, there is also some evidence that such behavior is culturally bounded ( Chow et al., 1997; Sharp and Salter, 1997; Greer and Stephens, 2001 ). This study extends previous findings on cross‐cultural differences in decision‐making among managers by comparing the responses of managers in the USA and Mexico to an escalation of commitment exercise. The cross‐cultural validity of two US based theories, agency (adverse selection) and framing (prospect theory), is tested. The results indicate that at base Mexican managers were more risk seeking. However managers from the more individualistic USA were significantly more likely than Mexican managers to escalate in the presence of agency (adverse selection) based incentives. Negative framing among managers was universal in escalating commitment.     

The Eurozone Crisis and Emerging‐Market Expansion: Capital Switching and the Uneven Geographies of Spanish Urbanization

The theory of capitalist urbanization posits that the built form serves as a crucial sink through which overaccumulated capital is ‘switched' from industrial production into long‐term investment in urban infrastructure. Since Harvey's (1978) deployment of the theory, researchers have attempted to empirically substantiate the switching thesis with limited success. Christophers (2011) revisited the debate with new data and methods to support the claim that significant investment had switched into the built environment at the onset of the 2007/08 financial crisis. However, Christophers' study overlooks how crises are also geographically displaced. This article analyses Spanish trade data for the years 1993 to 2013, the years prior and subsequent to the housing‐induced economic crisis (1997 to 2006). Two studies are undertaken. The first replicates Christophers' methodology to assess how and to what extent a sectoral switch into property investment occurred in Spain between 1997 and 2006. The second modifies the methodology to investigate the extent to which overaccumulated capital in Spain has been geographically displaced through investment in the Moroccan building industry since 2006. These approaches situate uneven development (geographical switching) and turnover time (sectoral switching) as the twin dynamics through which capitalist urbanization is spatio‐temporally fixed.     

Measuring Business Cycles Intra‐Synchronization in US: A Regime‐switching Interdependence Framework

This paper proposes a Markov‐switching framework to endogenously identify periods where economies are more likely to (i) synchronously enter recessionary and expansionary phases, and (ii) follow independent business cycles. The reliability of the framework is validated with simulated data in Monte Carlo experiments. The framework is applied to assess the time‐varying intra‐country synchronization in the US. The main results report substantial changes over time in the cyclical affiliation patterns of US states, and show that the more similar the economic structures of states, the higher the correlation between their business cycles. A synchronization‐based network analysis discloses a change in the propagation pattern of aggregate contractionary shocks across states, suggesting that the US has become more internally synchronized since the early 1990s.     

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis–Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models—a fixed effects model and a random effects model—are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.     

Large time‐varying parameter VARs: A nonparametric approach

In this paper we introduce a nonparametric estimation method for a large Vector Autoregression (VAR) with time‐varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs. When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and compares well with large (parametric) Bayesian VARs with time‐varying parameters. The tool can also be used for structural analysis. As an example, we study the time‐varying effects of oil price shocks on sectoral U.S. industrial output. According to our results, the increased role of global demand in shaping oil price fluctuations largely explains the diminished recessionary effects of global energy price increases.     

Barriers to cross‐border trade union cooperation in Europe: the case of the graphical workers

This paper is concerned with exploring the barriers to cross‐border trade union cooperation among graphical workers in Europe. Highlighting the increasing globalisation of graphical multinationals, the paper illustrates that graphical unions cannot restrict their activities to developments within national boundaries. As such it highlights some of the obstacles that unions face in attempting to instigate transnational cooperation strategies. These obstacles include: the role of employers, the prevailing practices of the unions, employee reticence, the role of the law and resource constraints. It concludes by stressing the continuing need to strengthen cross‐border trade union networks with the ability to impose effective sanctions against the unbridled growth of multinational power.     

Estimation of Common Factors under Cross‐Sectional and Temporal Aggregation Constraints

The paper estimates a large‐scale mixed‐frequency dynamic factor model for the euro area, using monthly series along with gross domestic product (GDP) and its main components, obtained from the quarterly national accounts (NA). The latter define broad measures of real economic activity (such as GDP and its decomposition by expenditure type and by branch of activity) that we are willing to include in the factor model, in order to improve its coverage of the economy and thus the representativeness of the factors. The main problem with their inclusion is not one of model consistency, but rather of data availability and timeliness, as the NA series are quarterly and are available with a large publication lag. Our model is a traditional dynamic factor model formulated at the monthly frequency in terms of the stationary representation of the variables, which however becomes nonlinear when the observational constraints are taken into account. These are of two kinds: nonlinear temporal aggregation constraints, due to the fact that the model is formulated in terms of the unobserved monthly logarithmic changes, but we observe only the sum of the monthly levels within a quarter, and nonlinear cross‐sectional constraints, since GDP and its main components are linked by the NA identities, but the series are expressed in chained volumes. The paper provides an exact treatment of the observational constraints and proposes iterative algorithms for estimating the parameters of the factor model and for signal extraction, thereby producing nowcasts of monthly GDP and its main components, as well as measures of their reliability.     

Social Intermediation in Base‐of‐the‐Pyramid Markets

Our study explores the structuring decisions made by intermediaries seeking to alleviate poverty by connecting base‐of‐the‐pyramid markets with more developed markets. Using intermediation theory to ground our study, we collected qualitative data on 29 social intermediation projects located within Latin America, Africa, and Asia. Our findings suggest that ‘socializing’ intermediation theory to more accurately explain and predict structural outcomes across more diverse contexts requires three key modifications: (1) the attenuation of opportunism, which creates an internalizing social force; (2) the accommodation of non‐monetary objectives, which creates an externalizing social force; and (3) the perception of transaction capabilities as tractable, which serves as a guidepost for reconciling these two opposing social forces.     

Small‐sample confidence intervals for multivariate impulse response functions at long horizons

Existing methods for constructing confidence bands for multivariate impulse response functions may have poor coverage at long lead times when variables are highly persistent. The goal of this paper is to propose a simple method that is not pointwise and that is robust to the presence of highly persistent processes. We use approximations based on local‐to‐unity asymptotic theory, and allow the horizon to be a fixed fraction of the sample size. We show that our method has better coverage properties at long horizons than existing methods, and may provide different economic conclusions in empirical applications. We also propose a modification of this method which has good coverage properties at both short and long horizons. Copyright © 2006 John Wiley & Sons, Ltd.     

Macroeconomic Forecasting Performance under Alternative Specifications of Time‐Varying Volatility

This paper compares alternative models of time‐varying volatility on the basis of the accuracy of real‐time point and density forecasts of key macroeconomic time series for the USA. We consider Bayesian autoregressive and vector autoregressive models that incorporate some form of time‐varying volatility, precisely random walk stochastic volatility, stochastic volatility following a stationary AR process, stochastic volatility coupled with fat tails, GARCH and mixture of innovation models. The results show that the AR and VAR specifications with conventional stochastic volatility dominate other volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree. Copyright © 2014 John Wiley & Sons, Ltd.     

Euro‐insurance‐bonds: a long‐term solution for the European sovereign debt problem?

This article proposes that all new Euro area sovereign borrowing be in the form of jointly underwritten ‘Euro‐insurance‐bonds’ trading at the same price for outside investors. To avoid classic moral hazard problems and to insure the guarantors against default, each country would pay a risk premium conditional on economic fundamentals to a joint debt management agency…     

Steady‐state modeling and macroeconomic forecasting quality

Vector autoregressions (VARs) with informative steady‐state priors are standard forecasting tools in empirical macroeconomics. This study proposes (i) an adaptive hierarchical normal‐gamma prior on steady states, (ii) a time‐varying steady‐state specification which accounts for structural breaks in the unconditional mean, and (iii) a generalization of steady‐state VARs with fat‐tailed and heteroskedastic error terms. Empirical analysis, based on a real‐time dataset of 14 macroeconomic variables, shows that, overall, the hierarchical steady‐state specifications materially improve out‐of‐sample forecasting for forecasting horizons longer than 1 year, while the time‐varying specifications generate superior forecasts for variables with significant changes in their unconditional mean.