Mark Kritzman, Simon Myrgren, and Sebastien Page
A technique called dynamic programming can be used to identify an optimal rebalancing schedule, which significantly reduces rebalancing and sub-optimality costs. Dynamic programming provides solutions to multi-stage decision processes in which the decisions made in prior periods affect the choices available in later periods. Dynamic programming provides the optimal year-by-year decision policy by working backwards from year 10. The results of the test of the relative efficacy of dynamic programming and the MvD heuristic with data on domestic equities, domestic fixed income, non-US equities, non-US fixed income, and emerging market equities, show that the MvD heuristic performs quite well compared to the dynamic programming solution for the two-asset case and substantially better than other heuristics. The increase in the number of assets reduces the advantage of dynamic programming over the MvD heuristic and is reversed at the level of five assets. Dynamic programming cannot be applied beyond five assets, but the MvD heuristic can be extended up to 100 assets. The MvD heuristic reduces total costs relative to all of the other heuristics by substantial amounts. The performance of the MvD heuristic improves relative to the dynamic programming solution as more assets are added but this improvement reflects a growing reliance on an approximation for the dynamic programming approach.
Halvor Mehlum and Karl Moene
This article explores the tendency for poverty and conflict, as well as for prosperity and peace, to reinforce one another, examining two specific factors. One is the type of rents that adversaries may contest, as rents can differ in terms of the vulnerability of their value to conflict; more vulnerable rents tend to induce more peace, whereas less vulnerable rents have the opposite effect. The second factor concerns the relationship between the elites and the entrepreneurs in their respective groups—specifically, the extent to which the elites care about their entrepreneurs. While these two factors can predispose countries to either virtuous or vicious circles, multiple equilibria are also possible.
Petter N. Kolm and Lee Maclin
This article discusses the portfolio optimization with market impact costs, combining execution and portfolio risk, and dynamic portfolio analysis. A multi-period portfolio optimization model is proposed that incorporates permanent and temporary market impact costs, and alpha decay. There are five popular algorithmic trading strategies that include arrival price, market-on-close, participation, time-weighted average price (TWAP), and volume-weighted average price (VWAP). For a VWAP benchmark, the lowest risk execution is obtained by trading one's own shares in the same fractional volume pattern as the market. VWAP execution is expected to result in the lowest temporary market impact costs. The temporary market impact in a rate of trading model is a function of one's own rate of trading expressed as a fraction of the absolute trading activity of the market. One popular interpretation of the model is that the markets are relatively efficient with respect to the relationship between trading volume and volatility, which are typical inputs of the model. Any reduction in impact that results from more trading volume would be offset by an increase in impact due to increased volatility. The lowest absolute rate of trading can be realized by distributing one's orders evenly over time. This is called a time-weighted average price (TWAP) execution.
This chapter reviews recent developments in the analysis of macroeconomic panel data which typically involve aggregate variables from various countries. In contrast to the large N, small T framework that characterizes microeconomic panels, the two dimensions of a macroeconomic data set are more balanced, often providing a comparable number of time periods and countries (regions). Although this is inconsequential for the analysis based on the linear static panel data framework, it becomes crucial when estimating a dynamic model. A second important feature of macroeconomic data is cross-section dependence among countries. In many cases this dependence cannot be accommodated by a simple function of the geographical distance but also depends on trade relations and the level of economic development. Furthermore, cross-country data often exhibit a much richer pattern of heterogeneity that cannot be represented just by letting the intercept vary across countries. While it is often infeasible to allow for individual specific regression coefficients in a large N, small T panel framework, this may be a reasonable option when analyzing macroeconomic data.
Antony Davies, Kajal Lahiri, and Xuguang Sheng
This article illustrates how frameworks built around multidimensional panel data of forecasts can be used not only to test the rational expectations hypothesis correctly, but also to study alternative expectations-formation mechanisms, to distinguish anticipated from unanticipated shocks, and to distinguish forecast uncertainty from disagreement.
Applying Experiments to Land Economics: Public Information and Auction Efficiency in Ecosystem Service Markets
Kent D. Messer, Joshua M. Duke, and Lori Lynch
The use of laboratory and field economic experiments to explore issues in land economics is increasingly popular as researchers identify problems that cannot be adequately addressed by traditional economic theory or empirical techniques. This article reviews this area’s growing literature as well as offers a framework to understand the trade-offs between issues of experimental control, problem context, and representativeness of participants. The key experiment design elements related to land economics are discussed. These elements are then illustrated by a study of the efficiency of reverse auctions for land conservation given different structures of private and public information. The study results suggest that different levels of public information affect sellers’ bidding behavior as well as competitiveness. Overbidding and too little market competition leads to significant loss of efficiency. These results have implications to how to design ecosystem service market cost effectively.
Giorgio d'Agostino, J. Paul Dunne, and Luca Pieroni
The earlier literature regarding the effects of military expenditures on economic growth had initially shown a positive relationship between the two variables. This article examines this topic, taking account of more recent models of growth. The second section considers the alternative general economic theories that inform the development of models to undertake empirical analyses. The third section considers estimation issues. The fourth section considers the alternative formal models that are common in the literature: the Feder–Ram model, the modified Solow model, and the endogenous growth models. The fifth section presents some empirical results to illustrate the issues involved in estimating the models and to compare their performance. The estimation of more sophisticated models indicates, contrary to the early studies, that the effect of military expenditures on growth is negative.
Elena G. Irwin and Douglas H. Wrenn
This chapter provides a targeted review and assessment of current empirical methods most commonly used in economics to model spatially explicit land use and land use change. Empirical models are broadly defined as those that use data on land use and the underlying demand and supply processes to specify model parameters in some way. Four main types of modeling methods are considered: reduced-form econometric, structural econometric, spatial equilibrium simulation, and agent-based simulation. Key strengths and weaknesses of each method are discussed, and the applicability of each method for answering various research questions, including policy scenarios, is illustrated with a few recent examples from the literature. The chapter concludes with a discussion of potential complementarities among these various approaches and several critical research gaps.
Francis Breedon and Robert Kosowski
The article aims to discuss the optimal asset allocation for sovereign wealth funds (SWF). The main purpose of a commodity based sovereign wealth fund is to create a permanent income stream out of a temporary one and so allow consumption smoothing over time. The asset allocation framework typically consists of an objective function that implies a preference for the highest return for a given level of risk. The ultimate objective of a SWF is to smooth consumption and achieve intergenerational transfers. The accumulation of financial assets presupposes functioning markets for consumption goods such as food products. Another consideration that may guide the investment behavior of sovereign wealth funds and that highlights the role of liabilities is food security. Future food imports are a key component of the balance of payments identity. A rigorous analysis of the commodity fund's optimal asset allocation policy must take into account the role of liabilities and therefore requires an analysis of the country's balance of payments. The ALM takes into account the role of liabilities and the resulting additional hedging demands. The asset liability management (ALM) examines both assets and financial liabilities and models the return on assets and the return on liabilities.
Marine Carrasco, Jean-Pierre Florens, and Eric Renault
This chapter studies the estimation of φ in linear inverse problems Tφ = r, where r is only observed with error and T may be given or estimated. The unknown element φ belongs to a Hilbert space E. Four examples are relevant for econometrics: the density estimation, the deconvolution problem, the linear regression with an infinite number of possibly endogenous explanatory variables, and the nonparametric instrumental variables estimation. In the first two cases T is given, whereas it is estimated in the two other cases, respectively at a parametric or nonparametric rate. This chapter will recall the main results on these models: concepts of degree of ill-posedness, regularity of φ, regularized estimation, and the rates of convergence usually obtained. The main contributions are, moreover, related to the asymptotic normality of the regularized solution φ obtained with a regularization parameter α. If α → 0, we particularly consider the asymptotic normality of inner products <φ, ϕ>, where ϕ is an element of E. These results can be used to construct (asymptotic) tests on φ.