SMEs and public procurement policy

In this paper, we characterize an optimal procurement policy as a mechanism design problem when an allotment of the contract is available, i.e., when a government faces both SMEs and large firms for carrying out a heterogeneously divisible project. Our model allows us to analyze all procurement policies (set-asides, favoritism, non-discriminatory rules), taking into account both efficiency and distributive arguments and derive a normative framework. We show that set-asides are not generally optimal, whatever the industrial preferences of the government are, while the optimal preferential treatments of firms implies complex non-linear rules. We prove that the optimal policy can be implemented using a modified Vickrey-type auction. We also consider that the firms can reduce their cost by a non observable effort, and exhibit the specific impact of cost reduction incentives on the optimal policies.Received: 24 September 2001, JEL Classification: D44Pierre-HenriMorand : I am grateful to the anonymous referees for comments. The usualdisclaimer applies.     

Tax shocks with high and low uncertainty

We assess whether the effects of fiscal policy depend on the extent of uncertainty in the economy. Focusing on tax shocks, identified by the narrative series by Romer and Romer (American Economic Review, 2010, 100(3), 763‐801), and various measures of uncertainty, we use a Threshold VAR model to allow for dependence of the effects of the tax shocks on both the level of uncertainty and the sign of the shock. We find that the economy responds more positively to tax cuts during periods of low uncertainty, while, in response to tax increases, the response of main aggregates is more negative in more uncertain times. We argue that controlling for monetary policy in fiscal VARs is important to avoid omitted variable bias. We interpret our empirical evidence in light of existing theoretical contributions.     

Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP*

In this article, we merge two strands from the recent econometric literature. First, factor models based on large sets of macroeconomic variables for forecasting, which have generally proven useful for forecasting. However, there is some disagreement in the literature as to the appropriate method. Second, forecast methods based on mixed‐frequency data sampling (MIDAS). This regression technique can take into account unbalanced datasets that emerge from publication lags of high‐ and low‐frequency indicators, a problem practitioner have to cope with in real time. In this article, we introduce Factor MIDAS, an approach for nowcasting and forecasting low‐frequency variables like gross domestic product (GDP) exploiting information in a large set of higher‐frequency indicators. We consider three alternative MIDAS approaches (basic, smoothed and unrestricted) that provide harmonized projection methods that allow for a comparison of the alternative factor estimation methods with respect to nowcasting and forecasting. Common to all the factor estimation methods employed here is that they can handle unbalanced datasets, as typically faced in real‐time forecast applications owing to publication lags. In particular, we focus on variants of static and dynamic principal components as well as Kalman filter estimates in state‐space factor models. As an empirical illustration of the technique, we use a large monthly dataset of the German economy to nowcast and forecast quarterly GDP growth. We find that the factor estimation methods do not differ substantially, whereas the most parsimonious MIDAS projection performs best overall. Finally, quarterly models are in general outperformed by the Factor MIDAS models, which confirms the usefulness of the mixed‐frequency techniques that can exploit timely information from business cycle indicators.     

Risk management under a prudential policy

In this paper, we study the structure of optimal contracts in banking system when there is no risk of moral hazard. We consider a risk management problem under a policy that reduces the excessive risk-taking behavior by making all banks bear part of the risk that they transfer to other parties in the market. First, we characterize the optimal solutions to the risk management problem, and, second, we find a necessary and sufficient condition under which the “risk of the tail events” will not be transferred. In particular, we will study the problem using two known risk measures, value at risk and conditional value at risk, and will show that in these cases, the optimal solutions are in the form of stop-loss policies.     

The relationship between quality management and new product development: evidence from China

Research suggests that organizations involved in new product development (NPD) can adopt quality management (QM) systems to optimize their NPD processes and thereby build their NPD competence. This paper contributes to a further understanding of the link between QM and NPD by investigating why and how more effective QM can promote and assist NPD. Based on taxonomy of QM practices, we examine the differences between the effects of infrastructure quality management practices (IQMP) and core quality management practices (CQMP) on a firm’s NPD capability and NPD performance. We also incorporate NPD practices in a conceptual model, to examine the integration effects of QM practices and NPD practices. The results show that IQMP significantly promotes NPD capability, while the influence of CQMP on NPD capability is relatively insignificant. Furthermore, our results indicate that the integration of design and manufacturing has a significant negative influence on NPD capability. Our findings highlight the significant role NPD capability plays in explaining the link between QM practices and NPD performance. Our findings also suggest to practitioners that they should integrate QM with other technology management practices in order to optimize their NPD processes.     

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Learning-by-doing versus Schooling in a Model of Endogenous Growth

A two sector model of learning-by-doing measured by means of production aggregated over time and of human capital accumulation in a schooling sector is presented. Time utilization is rival between schooling and learning-by-doing. Depending on the sum of elasticities of the accumulated factors (i.e., of production experience and educational human capital) in both sectors, a situation with or without endogenous growth results. Dynamic optimization of the choice between leisure and working and of the division of human capital between education and production is executed. Transitional dynamics are analyzed for a Cobb-Douglas example and a numerical simulation is performed.JEL classification: C61, D90, O41.Acknowledgements The author would like to thank Eric C. Meyer and two anonymous referees for helpful comments. The usual caveats apply.revised version received November 23, 2003