Evaluating expectations of <Emphasis Type="Italic">L</Emphasis>-statistics by the Steffensen inequality

By combining the Moriguti and Steffensen inequalities, we obtain sharp upper bounds for the expectations of arbitrary linear combinations of order statistics from iid samples. The bounds are expressed in terms of expectations of the left truncated parent distribution and constants that depend only on the coefficients of the linear combination. We also present analogous results for dependent id samples. The bounds are especially useful for L-estimates of the scale parameter of the distribution.     

The Feldstein–Horioka puzzle in Latin American and Caribbean countries: a panel cointegration analysis

In this paper, the recently developed panel unit root and the Pedroni cointegration tests are applied to empirically examine the validity of the Feldstein–Horioka puzzle (F–H puzzle) for a heterogeneous panel of 14 Latin American and five Caribbean countries over the period, 1960–2002. The findings indicate that in these countries, the long-run solvency condition is maintained. Finally, employing the Pedroni panel group FM-OLS estimator (2000, 2001), it is found that the statistically significant estimated savings-retention coefficient for the panel is relatively small indicating that the F–H Puzzle is not valid and thus implying the prevalence of a moderate degree of capital mobility.

MULTIVARIATE METHODS FOR MONITORING STRUCTURAL CHANGE

Detection of structural change is a critical empirical activity, but continuous ‘monitoring’ for changes in real time raises well‐known econometric issues that have been explored in a single series context. If multiple series co‐break then it is possible that simultaneous examination of a set of series helps identify changes with higher probability or more rapidly than when series are examined on a case‐by‐case basis. Some asymptotic theory is developed for maximum and average CUSUM detection tests. Monte Carlo experiments suggest that these both provide an improvement in detection relative to a univariate detector over a wide range of experimental parameters, given a sufficiently large number of co‐breaking series. This is robust to a cross‐sectional correlation in the errors (a factor structure) and heterogeneity in the break dates. We apply the test to a panel of UK price indices. Copyright © 2011 John Wiley & Sons, Ltd.     

An application of nonparametric volatility estimators to option pricing

We discuss the impact of volatility estimates from high frequency data on derivative pricing. The principal purpose is to estimate the diffusion coefficient of an Itô process using a nonparametric Nadaraya–Watson kernel approach based on selective estimators of spot volatility proposed in the econometric literature, which are based on high frequency data. The accuracy of different spot volatility estimates is measured in terms of how accurately they can reproduce market option prices. To this aim, we fit a diffusion model to S&P 500 data, and successively, we use the calibrated model to price European call options written on the S&P 500 index. The estimation results are compared to well-known parametric alternatives available in the literature. Empirical results not only show that using intra-day data rather than daily provides better volatility estimates and hence smaller pricing errors, but also highlight that the choice of the spot volatility estimator has effective impact on pricing.     

Note on the existence and modulus of continuity of the {\textit{SLE}}_8 curve

We review one method for estimating the modulus of continuity of a Schramm–Loewner evolution (SLE) curve in terms of the inverse Loewner map. Then we prove estimates about the distribution of the inverse Loewner map, which underpin the difficulty in bounding the modulus of continuity of SLE for $\kappa =8$ . The main idea in the proof of these estimates is applying the Girsanov theorem to reduce the problem to estimates about one-dimensional Brownian motion.     

The Eisner Puzzle,the Unemployment Threshold and the Range of Equilibria

Using a two-regime model of the inflation-unemployment process for US data 1960:2 to 2000:2, this paper finds strong evidence to support the Eisner puzzle, which occurs when the short-run Phillips curve (SRPC) is flatter at low rates of unemployment than at higher rates. The puzzling aspect of this pattern is the expectation of excess demand to become apparent at very low rates of unemployment causing the SRPC to be steep rather than fairly flat. We show the puzzle can be resolved by estimating a three-regime model which reveals a steep SRPC at very low rates of unemployment. The estimates of the three regime model also reveal a horizontal SRPC at intermediate rates of unemployment, implying the existence of a range of equilibrium rates of unemployment at those intermediate rates.

Fiscal consolidation with high growth: A policy simulation model for India

In this paper a fiscal consolidation program for India has been presented based on a policy simulation model that enables us to examine the macroeconomic implications of alternative fiscal strategies, given certain assumptions about other macro policy choices and relevant exogenous factors. The model is then used to estimate the outcomes resulting from a possible strategy of fiscal consolidation in the base case. The exercise shows that it is possible to have fiscal consolidation while at the same time maintaining high GDP growth of around 8% or so. The strategy is to gradually bring down the revenue deficit to zero by 2014–15, while allowing a combined fiscal deficit for centre plus states of about 6% of GDP. This provides the space for substantial government capital expenditure, which translates to a significant public investment program. This in turn leads to high overall investment directly and indirectly, via the crowding in effect on private investment, which drives the high GDP growth. The exercise has also tested the robustness of this strategy under two alternative scenarios of higher and lower advanced country growth compared to the base case.     

CIVIL WAR EXPOSURE AND VIOLENCE

In recent years scholars have begun to focus on the consequences of individuals' exposure to civil war, including its severe health and psychological consequences. Our innovation is to move beyond the survey methodology that is widespread in this literature to analyze the actual behavior of individuals with varying degrees of exposure to civil war in a common institutional setting. We exploit the presence of thousands of international soccer (football) players with different exposures to civil conflict in the European professional leagues, and find a strong relationship between the extent of civil conflict in a player's home country and his propensity to behave violently on the soccer field, as measured by yellow and red cards. This link is robust to region fixed effects, country characteristics (e.g. rule of law, per capita income), player characteristics (e.g. age, field position, quality), outliers, and team fixed effects. Reinforcing our claim that we isolate the effect of civil war exposure rather than simple rule breaking or something else entirely, there is no meaningful correlation between our measure of exposure to civil war and soccer performance measures not closely related to violent conduct. The result is also robust to controlling for civil wars before a player's birth, suggesting that it is not driven by factors from the distant historical past.     

COMMENT ON "THE IRREDUCIBLE ROLE OF DERIVED MARGINAL UTILITY IN DYNAMIC STOCHASTIC PROGRAMMING"

This comment shows why the Lagrange method can be simpler than dynamic programming in solving dynamic optimization problems.     

Socioeconomic predictors of forest use values in the Peruvian Amazon: A potential tool for biodiversity conservation

Conservation is a crisis discipline requiring rapid action with limited funds. This study examines the potential of socioeconomic variables to predict forest use values. If natural resource use can be predicted from socioeconomic data, conservation planners could rapidly identify and focus conservation programs on the sectors of local populations that most intensively utilize local flora and fauna. Families in three communities in the northern Peruvian Amazon were surveyed over a 6-month period. Data were collected on use of flora and fauna from six locally determined use categories (food, medicine and poisons, wood, weavings, adornments, and “other”) in forest types of three age classes (fallow fields—very young forests, young secondary forests, and old secondary forests). Forest use values were the dependant variables calculated in $/ha/year. Socioeconomic variables included: age, education, family size, residence time, land worked, land owned, number of fishing nets, chickens, pigs, cows, and/or mules owned (all proxies for productive assets), and level of ecological knowledge (ability of informants to correctly identify forest species and answer basic questions about their biology). Ordinary least square multiple regressions were run independently for each forest type. Regressions were also run separately for the two most valuable use categories, food and wood. Low R² adjusted values (all < 0.3) reflect the difficulty in predicting human behavior due to confounding variables and complex interactions. Residence time and a household's community of residence were the most significant predictors of forest use values. Households in Vista Alegre, the community with the highest density of people and smallest landholdings per household, extracted the highest value of forest products per hectare. The longer a family stayed in any community the higher the value of forest goods they extracted. If families that lived in an area longest are the most intensive extractors of forest products, they should be a major focus for conservation programming. In addition, the higher value of products extracted from forests by some families may make them more open to strategies seeking to protect long-term viability of the resources they utilize. The importance of residence time also indicates that planners need to account for changes in the resource use patterns of stakeholders over time.