Supplier dependence asymmetry and investment in innovation: The role of psychological uncertainty

A key source of competitive advantage for large firms accrues from investments in innovative products and processes by their suppliers, incentivized by a positive relationship climate. A fundamental hindrance lies in a condition that commonly characterizes buyer-supplier relationships: asymmetric levels of dependence between business partners. Such asymmetry has been shown to be detrimental to the relationship, enhancing the likelihood of conflict, and negatively impacting the performance of the more dependent party. Considering that such dependence asymmetry is likely to persist, large buyers face the challenge of promoting a relationship environment that provides an incentive for suppliers to invest in innovation. In this study, we propose that large, dominant buyers can influence suppliers' intentions and behaviors by mitigating the effects of their perceived riskiness and ambiguity that emerge from a situation of dependence asymmetry. Specifically, using the lens of resource dependence theory, we investigate the effects of these two psychological dimensions of uncertainty on a supplier's trust, commitment, and willingness to invest in innovation, as well as the moderating effect of a buyer's information sharing in shaping a supplier's perceived uncertainty. The model is tested with a scenario-based experiment and results are corroborated by interviews with experienced managers of retail suppliers. Our findings indicate that a supplier's dependence on a large buyer increases its perception of ambiguity and riskiness in the relationship, negatively impacting its trust, commitment, and willingness to invest in innovation. However, a buyer who shares relevant and timely information with the supplier mitigates its perceived uncertainty, promoting the supplier's positive attitudes towards the buyer and incentivizing innovation. Sharing operational and strategic information such as point-of-sales data, sales forecasts, or strategic plans, becomes a valuable strategy to powerful buyers in the pursuit of becoming a preferred customer and enhancing a supplier's resource mobilization towards the relationship.     

Growth,deficits and uncertainty: Theoretical aspects and empirical evidence from a panel of 27 countries

We examine the relationship between fiscal deficits and per-capita income growth in a panel of 27 European countries, allowing for perceived risks, in terms of fiscal sustainability, associated with additional government spending. Such risks are proxied by the conditional variability of manufacturing production and stock market returns and by the unconditional variability of two survey-based economic-sentiment indicators. To help clarifying how fiscal variables impact on growth and to provide a point of reference for the interpretation of the empirical results a structural growth model is first identified. We find evidence of an asymmetric relationship, in that fiscal deficits give rise to adverse growth effects if they coincide with high uncertainty regarding the prospects of the economy and no significant negative growth effects in the low-uncertainty case.     

Crises, portfolio flows, and foreign direct investment: An application to Turkey

We analyze how financial and economic crises affect the relation between the components of capital flows and their determinants in an emerging economy. Our results suggest that the composition of capital flows matters, crises can explain the volatility of portfolio flows and foreign direct investment, and modeling them as endogenous breakpoints improves the results considerably. By using data from the Turkish economy, we estimate these breakpoints together with the parameters of the model and find that they correspond to international and domestic crises that hit the country. Although both components are affected by similar crises, direct investment reacts strongly to the domestic crisis, while portfolios flows are more sensitive to global financial conditions. Breaks also have an effect on the significance and sign of determinants of each type of international investment. Evidence indicates changes in all coefficients in both investment types and suggests that analyses assuming parameter constancy lead to misleading results if they ignore the influence of endogenous breaks.     

Equilibrium dynamics in a class of one-sector endogenous growth models with external habits: An application of special functions

This paper analyzes the equilibrium dynamics in a class of one-sector endogenous growth models with external habits. Using an explicit solution expressed in terms of the Gauss hypergeometric function, we show that the levels of consumption, habits and capital may exhibit non-monotonic transition dynamics, even though their ratios converge monotonically. A numerical simulation illustrates this result.     

Popularity of reinforcement-based and belief-based learning models: An evolutionary approach

In an evolutionary model, players from a given population meet randomly in pairs each instant to play a coordination game. At each instant, the learning model used is determined via some replicator dynamics that respects payoff fitness. We allow for two such models: a belief-based best-response model that uses a costly predictor, and a costless reinforcement-based one. This generates dynamics over the choice of learning models and the consequent choices of endogenous variables. We report conditions under which the long run outcomes are efficient (or inefficient) and they support the exclusive use of either of the models (or their co-existence).     

Term structure models and the zero bound: An empirical investigation of Japanese yields

When Japanese short-term bond yields were near their zero bound, yields on long-term bonds showed substantial fluctuation, and there was a strong positive relationship between the level of interest rates and yield volatilities/risk premiums. We explore whether several families of dynamic term structure models that enforce a zero lower bound on short rates imply conditional distributions of Japanese bond yields consistent with these patterns. Multi-factor “shadow-rate” and quadratic-Gaussian models, evaluated at their maximum likelihood estimates, capture many features of the data. Furthermore, model-implied risk premiums track realized excess returns during extended periods of near-zero short rates. In contrast, the conditional distributions implied by non-negative affine models do not match their sample counterparts, and standard Gaussian affine models generate implausibly large negative risk premiums.     

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks

Likelihoods and posteriors of instrumental variable (IV) regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating posterior probabilities and marginal densities using Monte Carlo integration methods like importance sampling or Markov chain Monte Carlo procedures the speed of the algorithm and the quality of the results greatly depend on the choice of the importance or candidate density. Such a density has to be ‘close’ to the target density in order to yield accurate results with numerically efficient sampling. For this purpose we introduce neural networks which seem to be natural importance or candidate densities, as they have a universal approximation property and are easy to sample from. A key step in the proposed class of methods is the construction of a neural network that approximates the target density. The methods are tested on a set of illustrative IV regression models. The results indicate the possible usefulness of the neural network approach.     

An empirical comparison of the Tucker-Messick and INDSCAL models: Measuring viewpoints about transit attributes

This investigation sought (1) to identify perceptually homogenous respondent groups by two individual differences scaling models initially proposed by Tucker and Messick, and Carroll and Chang, (2) to reveal the significance of group percepts with respect to anticipated satisfactions and socio-economic and activity pattern characteristics of group members, and (3) to test empirically the significance of formal distinctions between the two individual differences models. The study utilized judgments about 12 transit attributes of three innovative urban, public transportation modes from a sample of 243 respondents. It was possible to specify seven perceptually homogenous groups, which were distinct in terms of a qualitative analysis of their perceptual spaces and a quantitative convergent-discriminant validity analysis predicated on the distances between pairs of attributes in their spaces. The perceptual groups were shown to have interpretable links to socio-economic and activity pattern characteristics of the respondents. In addition, it was possible to statistically account for the satisfaction ratings of the respondents by the dimensions of their corresponding spaces. Since the Tucker-Messick model was shown to derive more distinct spaces for the separate groups than the INDSCAL model of Carroll and Chang, the Tucker-Messick spaces more uniquely tied a group's percepts to its corresponding satisfactions.     

The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting

Does the use of information on the past history of the nominal interest rates and inflation entail improvement in forecasts of the ex ante real interest rate over its forecasts obtained from using just the past history of the realized real interest rates? To answer this question we set up a univariate unobserved components model for the realized real interest rates and a bivariate model for the nominal rate and inflation which imposes cointegration restrictions between them. The two models are estimated under normality with the Kalman filter. It is found that the error-correction model provides more accurate one-period ahead forecasts of the real rate within the estimation sample whereas the unobserved components model yields forecasts with smaller forecast variances. In the post-sample period, the forecasts from the bivariate model are not only more accurate but also have tighter confidence bounds than the forecasts from the unobserved components model.     

Cooperation and conflict among nations: An application of multi-sample confirmatory factor analysis

The measurement of cooperation and conflict among nations differs greatly among several empirical studies of international relations. In the multidimensional approach to the measurement of both concepts, cooperation and conflict are considered to be unmeasured traits of various indicators in different areas of interest. Insight into the validity of the measurement theory can be gained from the fit of the estimated measurement model and from the estimates of the unknown parameters. These estimates are obtained through confirmatory factor analysis of data on observable policy Indicators of both concepts (see e.g., Jöreskog, 1969). The reliability of the estimated model can be investigated by means of multi-sample confirmatory factor analysis, which allows one to fit a specified model to several data sets simultaneously. Maximum likelihood estimates of the unknown parameters of one-sample and multi-sample confirmatory factor analysis models, based on data available in COPDAB, can be obtained by using the LISREL-VI program (see Jöreskog and Sörbom (1986). The results indicate that cooperation and conflict in foreign policies of nations have de-escalating effects upon each other.     

New technology,human resources and competitiveness in developing countries: the role of technology transfer

Technology transfer is widely seen as an important means by which developing countries can both acquire the technologies and develop the human resources needed to compete internationally. However, there are different types of technology transfer which may stimulate or inhibit local human resource development. Foreign direct investment may inhibit local human resource development unless the foreign partner is committed to the indigenous enterprise becoming internationally competitive. Technology transfer through licensing and off-the shelf purchase allows greater indigenous management autonomy which, together with the more direct exposure to international competitive forces, may be more conducive to indigenous human resource development.     

Restricted forecasting with VAR models: An analysis of a test for joint compatibility between restrictions and forecasts

A restricted forecasting compatibility test for Vector Autoregressive Error Correction models is analyzed in this work. It is shown that a variance–covariance matrix associated with the restrictions can be used to cancel out model dynamics and interactions between restrictions. This allows us to interpret the joint compatibility test as a composition of the corresponding single restriction compatibility tests. These tests are useful for appreciating the contribution of each and every restriction to the joint compatibility between the whole set of restrictions and the unrestricted forecasts. An estimated process adjustment for the test is derived and the resulting feasible joint compatibility test turns out to have better performance than the original one. An empirical illustration of the usefulness of the proposed test makes use of Mexican macroeconomic data and the targets proposed by the Mexican Government for the year 2003.     

The Employer’s Responsibility to Maintain a Safe and Healthful Work Environment: An Historical Review of Societal Expectations and Industrial Practices

As early as 1200 A.D., it has been common English law practice for a master to protect his/her servant. Throughout time, this practice has been tested and has evolved into our modern day obligation of the employer to assure the health and safety of his or her employees. This historical analysis reviews specific events that influenced the expectation that employers are responsible for workplace safety and health beginning before the Industrial Revolution and leading up to and through the implementation of the Occupational Safety and Health Administration (OSHA) in the United States. This review is divided into three time periods covering the era of industrialization and early recognition of occupational hazards (late 1800s–1949), the era of voluntary industrial standards and controls (1950–1969), and the modern era of federal regulation (1970–present). Also outlined are the several approaches the law has taken to addressing employer responsibility shifting from fault-based injury compensation to disease-specific prevention strategies, and then to a no-fault workmen’s compensation system, and finally to a mandatory minimum-requirement national legislation. Furthermore, the growth of the occupational safety and health profession is addressed as these systems acted as drivers to promote employer responsibility, and many employers hired health and safety professionals to ensure that they were upholding their responsibility to their employees.     

Cointegration,long-run structural modelling and weak exogeneity: Two models of the UK economy

Cointegration ideas as introduced by Granger in 1981 are commonly embodied in empirical macroeconomic modelling through the vector error correction model (VECM). It has become common practice in these models to treat some variables as weakly exogenous, resulting in conditional VECMs. This paper studies the consequences of different approaches to weak exogeneity for the dynamic properties of such models, in the context of two models of the UK economy, one a national-economy model, the other the UK submodel of a global model. Impulse response and common trend analyses are shown to be sensitive to these assumptions and other specification choices.     

Workers,communities, and industrial property: An emerging language of rights

Out of recent national debates and local struggles over plant closings, an alternative language of industrial property rights has emerged. This language places the rights of workers and communities above, or on a par with, those of owners and managers. While this new language of rights coexists with more traditional conceptions of owner/manager prerogatives, its emergence suggests that rights of property ownership, which are often seen as relatively immutable structural constraints upon the capitalist labor process, may themselves be contested and subject to change.     

On the equivalence of location choice models: Conditional logit, nested logit and Poisson

It is well understood that the two most popular empirical models of location choice - conditional logit and Poisson - return identical coefficient estimates when the regressors are not individual specific. We show that these two models differ starkly in terms of their implied predictions. The conditional logit model represents a zero-sum world, in which one region’s gain is the other regions’ loss. In contrast, the Poisson model implies a positive-sum economy, in which one region’s gain is no other region’s loss. We also show that all intermediate cases can be represented as a nested logit model with a single outside option. The nested logit turns out to be a linear combination of the conditional logit and Poisson models. Conditional logit and Poisson elasticities mark the polar cases and can therefore serve as boundary values in applied research.     

On the globalization of stock markets: An application of Vector Error Correction Model,Mutual Information and Singular Spectrum Analysis to the G7 countries

This paper analyzes stock market relationships among the G7 countries between 1973 and 2009 using three different approaches: (i) a linear approach based on cointegration, Vector Error Correction (VECM) and Granger Causality; (ii) a nonlinear approach based on Mutual Information and the Global Correlation Coefficient; and (iii) a nonlinear approach based on Singular Spectrum Analysis (SSA). While the cointegration tests are based on regression models and capture linearities in the data, Mutual Information and Singular Spectrum Analysis capture nonlinear relationships in a non-parametric way. The framework of this paper is based on the notion of market integration and uses stock market correlations and linkages both in price levels and returns. The main results show that significant co-movements occur among most of the G7 countries over the period analyzed and that Mutual Information and the Global Correlation Coefficient actually seem to provide more information about the market relationships than the Vector Error Correction Model and Granger Causality. However, unlike the latter, the direction of causality is difficult to distinguish in Mutual Information and the Global Correlation Coefficient. In this respect, the nonlinear Singular Spectrum Analysis technique displays several advantages, since it enabled us to capture nonlinear causality in both directions, while Granger Causality only captures causality in a linear way. The results also show that stock markets are closely linked both in terms of price levels and returns (as well as lagged returns) over the 36 years analyzed.     

Forecasting another’s enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice

In two experiments, participants received advice from another participant on a task either with a correct answer (intellective tasks) or without a correct answer (judgmental task), in which the participant had to make a forecast. In both experiments, the level of trust in the advisor and a perception of the advisor having similar values were important predictors of the acceptance of advice for a judgmental, taste forecast task, whereas advisor confidence was a more important predictor of the acceptance of advice on the intellective task. In Experiment 2, the face-to-face interactions between the decision-maker and the advisor were videotaped and coded. Advisors provided more information to decision-makers for the taste forecast than for the intellective task. Further, whether the advisor provided information to supplement their recommendation or not was a significant predictor of the acceptance of advice on the taste forecast, but not on the intellective task. The results are discussed in the context of previous research on advice, which has predominately used intellective tasks.     

Unemployment Duration: An Analysis of Incomplete,Completed, and Multiple Spells in Emilia-Romagna

Sets of incomplete and completed spells of unemployment wereobtained from the Italian Quarterly Labour Force Survey,carried out by ISTAT in Emilia-Romagna (1993:1–1995:1).The data were analysed through a proportional hazards modelwith a Weibull specification of the baseline hazard, includingboth unobserved heterogeneity applied to the scale parameterof the duration distribution, and telescoping effect to accountfor spikes in the distribution of unemployment spells.They were compared formally also with a non-proportional hazardmodel based on a log-logistic distribution of duration.The estimation of the parameters was carried out separately on bothcompleted spells and quarterly incomplete spells to ascertaindifferences and to envisage the potential seasonal effect.The results showed that the shape parameters changed over time.The parameters of each covariate proved to be statisticallystable over time and were also equal to the parameters ofthe completed spells model.Therefore, the analysis of incomplete spells is fairly feasiblewhen an even (closed form) baseline hazard function is suitablefor data.     

Roles, resources and benefits of intermediate organizations supporting triple helix collaborative R&D: The case of Precarn

Triple helix collaborations involving academia, government and industry are believed vital to the success of regional technology development. However, due to differences in culture, organizational functioning and incentive mechanisms as well as the different objectives of the various actors involved, such collaboration is difficult to create and sustain. A case study of the organization called Precarn, a collaborative, which manages a program of triple helix projects, is used here to illustrate how an intermediate organization can help triple helix partnerships towards the successful commercialization of new technologies. The paper contributes to the literature on managing R&D collaborations and innovation networks using organization theories to explain why and how collaborative intermediate organizations can facilitate successful technological adoption and commercialization across innovation networks.