Nature of comovements in US state and MSA housing prices

This study analyzes the time-varying nature and determinants of comovements in US housing prices using state and metropolitan statistical area (MSA) data. We employ dynamic factor models with time-varying loadings and stochastic volatility (DFM-TV-SV) to estimate the national, regional, and state factors. The time-varying factor loadings and stochastic volatility features enrich the dynamic factor model structures and are an effective tool to examine the comovements in housing prices. We find that the national factor is the dominant factor in explaining the movement of housing prices. The national factor accounts for 79% of the variation in state-level housing prices on average, with the greatest magnitude occurring during the housing boom and bust periods in many regions and states. We also find that the factors and synchronization effects are time-varying and heterogeneous across regions. The state-level housing prices contain higher national housing factor components in states with more diverse economies, higher wages and house prices, and lower unemployment rates. These findings shed light on the effectiveness of residential real estate diversification across the United States and the potential for elevated national housing risk amid economic downturns due to increased national housing price integration.     

The political economy of public research investment and commodity policies in agriculture: an empirical study

The paper tests a political economy theory of simultaneous government decision‐making on income redistribution through commodity policies and on public research investment in agriculture. We use data from 37 countries on agricultural protection and public agricultural research expenditures (PARI). The empirical results are consistent with the political economy hypotheses. The analysis suggest that structural changes in the economy have important effects on the political incentives for governments not only to subsidize or tax farmers, but also to invest in public agricultural research. Furthermore, the analysis supports the hypotheses that the impact of such structural changes on government decision‐making on PARI is non‐linear and conditional on other factors. Regarding the impact of political institutions, the results suggest that more democracy neither leads to more distortionary transfers (agricultural protection), nor to lower investment in public goods (PARI). ©2000 Elsevier Science B.V. All rights reserved.     

Economic development, institutional change, and the political economy of agricultural protection An econometric study of Belgium since the 19th century

This empirical study uses 100 years of annual data on 11 agricultural commodities from Belgium to measure the impact of structural changes coinciding with economic development and changes in political institutions on agricultural protection. The analysis shows that changes in agricultural protection are caused by a combination of factors. Governments have increased protection and support to farmers when world market prices for their commodities fell, and vice versa, offsetting market effects on producer incomes. Other economic determinants were the share of the commodities in total consumer expenditures (negative effect) and in total output of the economy (positive effect). With Belgium a small economy, there was no impact of the trade position. Changes in political institutions have affected agricultural protection. Democratic reforms which induced a significant shift in the political balance towards agricultural interests, such as the introduction of the one‐man‐one‐vote system, led to an increase in agricultural protection. The integration of Belgian agricultural policies in the Common Agricultural Policy in 1968 coincided with an increase in protection, ceteris paribus. Both institutional factors, related to changes in access to and information about the decision‐making at the EU level, and structural changes in the agricultural and food economy may explain this effect.     

Implied volatility and future portfolio returns

Prior studies find that the CBOE volatility index (VIX) predicts returns on stock market indices, suggesting implied volatilities measured by VIX are a risk factor affecting security returns or an indicator of market inefficiency. We extend prior work in three important ways. First, we investigate the relationship between future returns and current implied volatility levels and innovations. Second, we examine portfolios sorted on book-to-market equity, size, and beta. Third, we control for the four Fama and French [Fama, E., French, K., 1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56.] and Carhart [Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance, 52, 57–82.] factors. We find that VIX-related variables have strong predictive ability.     

Fixed-step anonymous overtaking and catching-up

We investigate criteria for evaluating infinite utility streams that satisfy fixed-step anonymity and include some notion of overtaking or catching-up. We do so in a generalized setting that does not require us to specify the underlying finite-dimensional criterion (e.g. utilitarianism or leximin). We present axiomatizations that rely on weaker axioms than those in the literature, and which in one case is new. We also provide a complete analysis of the relationships between the symmetric parts of these criteria and likewise for the asymmetric parts.     

Co-creation as a risk-sharing strategy for the development of innovative EUV lithography technology in the semiconductor industry

Co-creation is becoming an innovative way for new technology development (NTD). We propose a four-staged co-creation model drawn upon a backdrop of ‘knowledge cloud’ for value creation and long-term customer commitment resulting in risk-sharing associated with NTD. The model is elaborated through the case of a leading semiconductor lithography equipment manufacturer (ASML) developing a new extreme ultraviolet lithography technology by engaging the major stakeholders in customer co-investment programme. The model is generic and applicable to any technology-driven industry and may include more stakeholders of same or allied technology.