Dynamic redistribution of mitigation resources during influenza pandemics

The Institute of Medicine (IOM) has pointed out that the existing pandemic mitigation models lack the dynamic decision support capability. In this paper, we present a simulation optimization model to generate dynamic strategies for distribution of limited mitigation resources, such as vaccines and antivirals, over a network of regional outbreaks. The model has the capability to redistribute the resources remaining from previous allocations in response to changes in the pandemic progress. The model strives to minimize the impact of ongoing outbreaks and the expected impact of potential outbreaks, considering measures of morbidity, mortality, and social distancing, translated into the societal and economic costs of lost productivity and medical services. The model is implemented on a simulated H5N1 outbreak involving four counties in the state of Florida, U.S. with over four million inhabitants. The performance of our strategy is compared to that of a myopic distribution strategy. Sensitivity analysis is performed to assess the impact of variability of some critical factors on policy performance. The methodology is intended to support public health policy on effective distribution of limited mitigation resources.     

Revisiting the objectives of worker-managed firms: An empirical assessment

This paper provides new evidence on the objectives pursued by worker-managed firms (WMFs). The basic neoclassical model assumes that WMFs maximizes net income per member instead of total profits (Ward, 1958). Even though it has been largely criticized, the Ward model has dominated the self-management literature. Alternative models suggest that WMFs are not only concerned about income per worker but also about the level of employment. However, the empirical content of these competing theoretical models has been rarely analyzed. This paper contributes to fill this gap by estimating the parameters of a generic welfare function, following the methodology proposed by Craig and Pencavel (1993). These parameters determine the relative importance that a WMF places on income per worker vis-a-vis the level of employment. Estimates are based on a long micro-panel of Uruguayan firms covering the entire population of Uruguayan worker-managed firm and conventional firms in 31 3-digit sectors over the period April 1996-December 2005. Following a strictly neoclassical framework, but simply allowing a more general specification of the WMF goals, we show that the assumption of the basic neoclassical model of the WMF is misleading. Our results support the view that WMFs are concerned with both employment and income per worker.     

Do employment subsidies work? Evidence from regionally targeted subsidies in Turkey

This paper studies the effects on registered employment and number of registered establishments of two employment subsidy schemes in Turkey. We implement a difference-in-differences methodology to construct appropriate counterfactuals for the covered provinces. Our findings suggest that both subsidy programs did lead to significant net increases in registered jobs in eligible provinces (5%–13% for the first program and 11%–15% for the second). However, the cost of the actual job creation was high because of substantial deadweight losses, particularly for the first program (47% and 78%). Because of better design features, the second subsidy program had lower, though still significant, deadweight losses (27%–46%). Although constrained by data availability, the evidence suggests that the dominant effect of subsidies was to increase social security registration of firms and workers rather than boosting total employment and economic activity. This supports the theory that in countries with weak enforcement institutions, high labor taxes on low-wage workers may lead to substantial incentives for firms and workers to operate informally.     

Joint estimation using revealed and stated preference data: An application using a national forest

We combine contingent behaviour with travel cost data to estimate the change in the recreational use value of a National Forest due to quality and price changes. Instead of the usual improvement scenario, a hypothetical deterioration in the conditions of the forest due to a fire is considered. A dataset containing five observations for each respondent enabled the estimation of three models for which the number of scenarios differed. The results show that visitors are sensitive to price and quality changes and that in the forest fire scenario the intended number of trips would be reduced and that respondents would experience a welfare loss. Signs of inconsistency between preferences expressed by revealed and intended behaviour were found. This research also provides some indications that strategic bias affects answers to price changes.     

对话《现代主义之后的艺术史》 第二部分:艺术史终结了吗? 5、艺术批评与先锋艺术

浪漫主义艺术时代,历史艺术最后一次得到召唤,没有争议地被树立为当时艺术的典范:自此开始,艺术史成为学术标准,艺术研究者和艺术家分道扬镳。艺术研究者不再继续书写当下的艺术历史,过去对他们来说已经足够伟大和理想,他们只愿意在艺术中书写过去。想反,艺术家不再仅仅在过去中寻找榜样,他们向往更好的未来,向往一个不被永恒的过去掌控的未来。两方的目的相反,却都同样把过去提出来,对抗当下.一方把过去当做模仿的内容,另一方把过去当做逃离的条件。     

ECONOMIC RECESSIONS,BANKING REFORM AND THE FUTURE OF CAPITALISM1

In the 2010 London School of Economics and Political Science Hayek Memorial Lecture, the author argues that flaws in the design of the monetary and financial system were responsible for the global financial crisis and the subsequent recession. The crash reflected the unsustainable nature of the bubble induced by artificial credit expansion created by fractional‐reserve banking under the direction of central banks. Such boom–bust cycles will continue until radical reforms are implemented, including a 100% reserve requirement for demand deposits.     

HEGY Tests in the Presence of Moving Averages*

We analyze the asymptotic distributions associated with the seasonal unit root tests of Hylleberg et al. (1990) for quarterly data when the innovations follow a moving average process. Although both the t‐ and F‐type tests suffer from scale and shift effects compared with the presumed null distributions when a fixed order of autoregressive augmentation is applied, these effects disappear when the order of augmentation is sufficiently large. However, as found by Burridge and Taylor (2001) for the autoregressive case, individual t‐ratio tests at the semi‐annual frequency are not pivotal even with high orders of augmentation, although the corresponding joint F‐type statistic is pivotal. Monte Carlo simulations verify the importance of the order of augmentation for finite samples generated by seasonally integrated moving average processes.     

Regime shifts in stock–flow I(2)–I(1) systems: the case of US fiscal sustainability

In the last two decades, fiscal sustainability has been tested through the use of non‐stationary time series analysis. Two different approximations can be found in the literature: first, a univariate approach that has focused on the stochastic properties of the stock of debt and, second, a multivariate one that has focused on the long‐run properties of the flows of expenditures and revenues, i.e., in the stochastic properties of the deficit. In this paper we unify these approaches considering the stock–flow system that fiscal variables configure. Our approach involves working in an I(2) stochastic processes framework. Given the possibility of the existence of regime shifts in the sustainability of US deficit that the literature has pointed out, we develop a new statistic that can be applied to test several types of I(2) cointegration and multicointegration relationships allowing for regime shifts. To test for these kinds of changing long‐run relationships we propose the use of a residual‐based Dickey–Fuller class of statistic that accounts for one structural break. We show that consistent estimates of the break fraction can be obtained through the minimization of the sum of squared residuals when there is I(2) cointegration. The finite sample performance of the proposed statistic is investigated by Monte Carlo simulations. The econometric methodology is applied to assess whether the US fiscal deficit and debt are sustainable. Copyright © 2010 John Wiley & Sons, Ltd.     

Interpretation problems of the partial correlation with nonnormally distributed variables

The partial correlation is a commonly used measure for assessing the bivariate correlation of two quantitative variables after eliminating the influence of one or more other variables. The partial correlation is generally interpreted as the correlation that would result if the variables to be eliminated were fixed (not allowed to vary and influence the other variables), which is referred to in the statistical literature as conditional correlation. The present paper demonstrates, by means of theoretical derivations and practical examples, that when the assumption of multivariate normality is violated (e.g., as a result of nonlinear relationships among the variables investigated) the usual interpretation of the partial correlation coefficient will be basically incorrect. In extreme cases the value of the partial correlation coefficient may be strongly positive, close to 1, whereas the conditional correlation may have a large negative value. To solve this problem the paper suggests to partial out a certain function (in most cases the square) of the variables whose effects are to be eliminated if nonlinear relationships are likely to occur.     

Determining the MSE-optimal cross section to forecast

In this paper, we address the question of which subset of time series should be selected among a given set in order to forecast another series. We evaluate the quality of the forecasts in terms of Mean Squared Error. We propose a family of criteria to estimate the optimal subset. Consistency results are proved, both in the weak (in probability) and strong (almost sure) sense. We present the results of a Monte Carlo experiment and a real data example in which the criteria are compared to some hypothesis tests such as the ones by Diebold and Mariano (1995),  and  and Giacomini and White (2006).