Elections as takeover bids: Some agonistics concerning good government

Agency theory has been widely applied to the governance of business corporations and to good advantage. The formal framework of agency theory pertains as well to polities, wherein citizens are the principals and politicians the agents. Where takeover efforts occur irregularly for corporations, they occur at regular intervals through elections for polities. Timothy Besley’s Principled Agents uses the agency theory to argue that electoral competition will generally select competent and public-spirited politicians. This claim follows from his formal framework, but that framework ignores some questionable and unsettled matters that challenge Besley’s relatively roseate view of the qualitative character of electoral selection.      

Returns from social capital in open source software networks

Open Source Software projects base their operation on a collaborative structure for knowledge exchange in the form of provision or reception of information, expertise and feedback on the creation of source code. Here, we address the direction of these knowledge flows among projects throughout social networks and their impact on project success. We identify the roles of membership or contribution that individuals play within projects. We found that connections through contributors who bring their knowledge to the project, improve project success, and that connection through members, who transfer their knowledge towards other projects, enhance project success. Finally, we found that ties through shared membership and contributions hamper project success. The analysis of knowledge flows and their impact on project success imply a translation of returns from investment in social capital, where investment takes the shape of knowledge flows and the returns mean the projects’ diffusion over the network.

Agricultural impacts on water quality and implications for virtual water trading decisions

Research on the flow of virtual water associated with agricultural crop production and trade has focussed almost entirely on water quantity. It is pertinent to consider and quantify the opportunity costs in terms of reduced water quality associated with crop production. This paper investigates the impacts of water quality on virtual water trading by creating a proxy for water quality impacts by calculating the amount of water required to dilute nonpoint-source agrochemical inputs to relevant water quality guideline values. The quantity of water required for dilution of five agrochemicals (two nutrients; nitrogen and phosphorus and three insecticides; azinphos-methyl, chlorpyrifos and endosulfan) was estimated for five crops in South Africa (maize, wheat, sugar cane, citrus and cotton) and compared to consumption of irrigation water (blue water) and rainfall (green water) for the same crops. Results indicate that the volume of water required for dilution is similar to the total sum of green and blue water required for crop production, but significantly greater than blue water use (irrigation use). For all crops phosphorus losses require greater amounts of water for dilution than for nitrogen, while pesticides result in the greatest water quality use. Estimates of water quality use are based on assumptions for a number of input variables (i.e. fertilizer application rates, percentage loss of agrochemicals from cropped areas). A Monte Carlo analysis (5000 iterations) was run to randomly select input variables from within defined ranges. Water quality use was calculated and expressed as a factor of blue water use. For all crops the average factor indicated that the volume of water required for dilution of all agrochemicals was greater than that required for irrigation. The results of this study clearly indicate that the impacts of agriculture on water quality need to be considered in virtual water trading scenarios. The incorporation of a method to predict impacts on water quality provides a comparative tool which generates a more holistic frame of reference for decision making with regard to impacts on the water resource and virtual water trading.     

Volatility spill-overs in commodity spot prices: New empirical results

The classical rational expectations model of commodity markets implies that expected spot price risk is an explanatory variable in spot price regressions; and also that inventory carryover, which is reduced by a larger price variance, creates autoregressive conditional heteroscedastic processes in spot prices. In order to falsify/verify this theory, it has typically been assumed that the square root of the conditional variance of spot prices, a proxy for spot price risk, enters the conditional mean function of spot prices. Based on this simple representation, a typical but counter intuitive outcome has been that spot price risk has an insignificant impact on spot prices, see, e.g., Beck (Beck, S., 1993. A Rational Expectations Model of Time Varying Risk Premia in Commodities Futures Markets: Theory and Evidence. International Economic Review 34, 149–168, Beck, S., 2001. Autoregressive Conditional Heteroskedasticity in Commodity Spot Prices. Journal of Applied Econometrics 16, 115–132). In this paper, we propose an alternative functional relationship (from GARCH(1,1) to GARCH(1,1)-AR(m)) between spot price risk and spot prices that is fully supported by the classical rational expectations model, and based on this new representation we are able to provide stronger empirical support for Muth's rational expectation theory.     

PRIOR ELICITATION IN MULTIPLE CHANGE‐POINT MODELS*

This article discusses Bayesian inference in change‐point models. The main existing approaches treat all change‐points equally, a priori, using either a Uniform prior or an informative hierarchical prior. Both approaches assume a known number of change‐points. Some undesirable properties of these approaches are discussed. We develop a new Uniform prior that allows some of the change‐points to occur out of sample. This prior has desirable properties, can be interpreted as “noninformative,” and treats the number of change‐points as unknown. Artificial and real data exercises show how these different priors can have a substantial impact on estimation and prediction.     

Brotherhood of competition: Foreign Direct Investment and domestic mergers

We examine the effects of mergers on Foreign Direct Investment (FDI), and on shaping national policies regarding FDI. In this work we develop a partial equilibrium model of an oligopolistic industry in which a number of domestic and foreign firms compete in the market for a homogeneous good in a host country. It is assumed that the number of foreign firms is endogenous and can be affected by the government policy in the host country. The government sets the policy (subsidies) to maximise social welfare. We allow domestic mergers. Our main results suggest that when the host country government imposes discriminatory lump-sum subsidy in favor of foreign firms, a merger of domestic firms will increase the number of FDI if the subsidy level is exogenous. With an endogenous level of subsidy, a merger of domestic firms will decrease (increase) the welfare if the domestic firms are more (less) efficient.     

Is real per capita state personal income stationary? New nonlinear,asymmetric panel-data evidence

This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.     

A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy

This paper focuses on a new strand of research that uses stochastic approach for making spatial price comparisons. We propose a novel method to account for the presence of spatial dependencies in consumer prices and consequently in price indexes by imposing penalization conditions on the estimation of traditional CPD models leading to the spatially-penalized country-product-dummy (SP-CPD) model. The paper proposes an appropriate estimation strategy, which enables us to simultaneously estimate all the parameters in the model, including the smoothing parameter of the penalization term instead of determining it externally. In order to estimate spatial price indexes for areas lacking in price data, we suggest applying the kriging methodology to the price indexes obtained from the SP-CPD model. This new approach is applied to official Italian CPI data for constructing regional spatial price indexes for 2014. The results show that price levels are higher in the Northern-Central regions than in the South.     

Does Monetary Policy Affect Income Inequality in the Euro Area?

This paper examines how the ECB's expansionary monetary policy affects income inequality in 10 euro area countries over the period 1999–2014. We distinguish two channels—labor-market and financial—through which monetary policy can have distributional effects. The labor-market channel is captured by wages and employment and the financial channel by asset prices and returns. We find that expansionary monetary policy in the euro area reduces income inequality, especially in the periphery countries. The labor-market channel enhances the equalizing effect: monetary expansion reduces income inequality stronger by raising wages and employment. There is limited evidence for the financial channel.     

An empirical investigation of the effects of impact fees on housing and land markets

This paper presents the results from estimating the effects of development impact fees on the prices of new and existing single-family homes and undeveloped residential land using unique data for Dade County, FL. The results show that an additional US$1.00 of fees increases the price of both new and existing housing by about US$1.60 and reduces the price of land by about US$1.00. These findings are shown to be consistent with the new view but not the old view theory of impact fee incidence.