39,225 research outputs found

    Military spending and economic growth in China: a regime-switching analysis

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    This article has been made available through the Brunel Open Access Publishing Fund.This article investigates the impact of military spending changes on economic growth in China over the period 1953 to 2010. Using two-state Markov-switching specifications, the results suggest that the relationship between military spending changes and economic growth is state dependent. Specifically, the results show that military spending changes affect the economic growth negatively during a slower growth-higher variance state, while positively within a faster growth-lower variance one. It is also demonstrated that military spending changes contain information about the growth transition probabilities. As a policy tool, the results indicate that increases in military spending can be detrimental to growth during slower growth-higher growth volatility periods. © 2014 © 2014 The Author(s). Published by Taylor & Francis

    Dynamics of Transformation from Segregation to Mixed Wealth Cities

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    We model the dynamics of the Schelling model for agents described simply by a continuously distributed variable - wealth. Agents move to neighborhoods where their wealth is not lesser than that of some proportion of their neighbors, the threshold level. As in the case of the classic Schelling model where segregation obtains between two races, we find here that wealth-based segregation occurs and persists. However, introducing uncertainty into the decision to move - that is, with some probability, if agents are allowed to move even though the threshold level condition is contravened - we find that even for small proportions of such disallowed moves, the dynamics no longer yield segregation but instead sharply transition into a persistent mixed wealth distribution. We investigate the nature of this sharp transformation between segregated and mixed states, and find that it is because of a non-linear relationship between allowed moves and disallowed moves. For small increases in disallowed moves, there is a rapid corresponding increase in allowed moves, but this tapers off as the fraction of disallowed moves increase further and finally settles at a stable value, remaining invariant to any further increase in disallowed moves. It is the overall effect of the dynamics in the initial region (with small numbers of disallowed moves) that shifts the system away from a state of segregation rapidly to a mixed wealth state. The contravention of the tolerance condition could be interpreted as public policy interventions like minimal levels of social housing or housing benefit transfers to poorer households. Our finding therefore suggests that it might require only very limited levels of such public intervention - just sufficient to enable a small fraction of disallowed moves, because the dynamics generated by such moves could spur the transformation from a segregated to mixed equilibrium.Comment: 12 pages, 7 figure

    The Pricing of Home Mortgage Loans to Minority Borrowers: How Much of the APR Differential Can We Explain?

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    The public releases of the 2004 and 2005 HMDA data have engendered a lively debate over the pricing of mortgage credit and its implications regarding the treatment of minority mortgage borrowers. This research uses aggregated proprietary data provided by lenders and an endogenous switching regression model to estimate the probability of taking out a subprime mortgage, and annual percentage rate (APR) conditional on getting either a subprime or prime mortgage. The findings reveal that up to 90% of the African American APR gap, and 85% of the Hispanic APR gap, is attributable to observable differences in underwriting, costing, and market factors that appropriately explain mortgage pricing differentials. Although any potential discrimination is problematic and should be addressed, the analysis suggests that little of the aggregate differences in APRs paid by minority and non-minority borrowers are appropriately attributed to differential treatment.

    Can VAR models capture regime shifts in asset returns? a long-horizon strategic asset allocation perspective

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    In the empirical portfolio choice literature it is often invoked that through the choice of predictors that may closely track business cycle conditions and market sentiment, simple Vector Autoregressive (VAR) models could produce optimal strategic portfolio allocations that hedge against the bull and bear dynamics typical of financial markets. However, a distinct literature exists that shows that non-linear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. In this paper we examine whether and how simple VARs can produce empirical portfolio rules similar to those obtained under a range of multivariate Markov switching models, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem on US data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those typical of non-linear models that account for bull-bear dynamics and characterize the differences in the implied hedging demands for a long-horizon investor with constant relative risk aversion preferences. We conclude that most (if not all) VARs cannot produce portfolio rules, hedging demands, or out-of-sample performances that approximate those obtained from equally simple non-linear frameworks.Econometric models ; Vector autoregression ; Asset pricing ; Rate of return

    Network Models of Phage-Bacteria Coevolution

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    Bacteria and their bacteriophages are the most abundant, widespread and diverse groups of biological entities on the planet. In an attempt to understand how the interactions between bacteria, virulent phages and temperate phages might affect the diversity of these groups, we developed a novel stochastic network model for examining the co-evolution of these ecologies. In our approach, nodes represent whole species or strains of bacteria or phages, rather than individuals, with "speciation" and extinction modelled by duplication and removal of nodes. Phage-bacteria links represent host-parasite relationships and temperate-virulent phage links denote prophage-encoded resistance. The effect of horizontal transfer of genetic information between strains was also included in the dynamical rules. The observed networks evolved in a highly dynamic fashion but the ecosystems were prone to collapse (one or more entire groups going extinct). Diversity could be stably maintained in the model only if the probability of speciation was independent of the diversity. Such an effect could be achieved in real ecosystems if the speciation rate is primarily set by the availability of ecological niches.Comment: 8 pages, 6 figure
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