RETHINKING THE EFFECT OF IMMIGRATION ON WAGES

This paper calculates the effects of immigration on the wages of native US workers of various skill levels in two steps. In the first step we use labor demand functions to estimate the elasticity of substitution across different groups of workers. Second, we use the underlying production structure and the estimated elasticities to calculate the total wage effects of immigration in the long run. We emphasize that a production function framework is needed to combine own‐group effects with cross‐group effects in order to obtain the total wage effects for each native group. In order to obtain a parsimonious representation of elasticities that can be estimated with available data, we adopt alternative nested‐CES models and let the data select the preferred specification. New to this paper is the estimate of the substitutability between natives and immigrants of similar education and experience levels. In the data‐preferred model, there is a small but significant degree of imperfect substitutability between natives and immigrants which, when combined with the other estimated elasticities, implies that in the period from 1990 to 2006 immigration had a small effect on the wages of native workers with no high school degree (between 0.6% and +1.7%). It also had a small positive effect on average native wages (+0.6%) and a substantial negative effect (−6.7%) on wages of previous immigrants in the long run.     

OIL AND THE MACROECONOMY: A QUANTITATIVE STRUCTURAL ANALYSIS

We model an open economy where macroeconomic variables fluctuate in response to oil supply shocks, as well as aggregate demand and supply shocks generated domestically and abroad. We use several robust predictions of the model to identify five fundamental shocks underlying the fluctuations of the (real) oil price, the US activity and the global business cycle. The estimates show that supply shocks generated in the global economy explain the largest fraction of the oil price fluctuations, about four times more than canonical oil supply shocks. The correlation between oil prices and the US activity varies with the type of shock.     

BOOK TRANSLATIONS AS IDEA FLOWS: THE EFFECTS OF THE COLLAPSE OF COMMUNISM ON THE DIFFUSION OF KNOWLEDGE

We use book translations as a new measure of international idea flows and study the effects of Communism's collapse in Eastern Europe on these flows. Using novel data on 800,000 translations and difference‐in‐differences approaches, we show that while translations between Communist languages decreased by two thirds with the collapse, Western‐to‐Communist translations increased by a factor of 4 and quickly converged to Western levels. Convergence was more pronounced in the fields of applied and social sciences, and was more complete in Satellite and Baltic than in Soviet countries. We discuss how these patterns help us understand how repressive institutions and preferences towards Western European ideas shaped the international diffusion of knowledge.     

TRADE QUOTAS AND BUYER POWER,WITH AN APPLICATION TO THE E.U. NATURAL GAS MARKET

We consider a market in which domestic buyers negotiate contracts with foreign sellers, and explore how trade quotas can help to increase the buyers' countervailing power. We use the Shapley value to describe bargaining power and the distribution of the trade surplus in such a bilateral oligopoly. By exploiting strategic externalities among the buyers, bilateral trade quotas can improve the buyers' bargaining positions. In contrast, aggregate trade restrictions on all buyers' trade never improve buyer surplus. Minimum quotas on imports from fringe suppliers can benefit nonaffected buyers, as these enjoy positive externalities. We apply these insights to the E.U. market for natural gas and show that the effects of trade quotas on E.U. gas importers' power can be significant.     

基于DSP和LabVIEW的多通道数据采集系统的设计

系统使用飞思卡尔的DSP56F807代替了数据采集卡,使用CodeWarrior软件的PE软件包开发DSP,通过串口通讯将其与NI公司的LabVIEW软件相结合,使用LabVIEW软件处理数据,从而实现了被测系统多通道数据的采集。实验证明,此系统工作迅速可靠。     

Ordered ranked set samples and applications to inference

Ranked set sampling (RSS) was first proposed by McIntyre [1952. A method for unbiased selective sampling, using ranked sets. Australian J. Agricultural Res. 3, 385–390] as an effective way to estimate the unknown population mean. Chuiv and Sinha [1998. On some aspects of ranked set sampling in parametric estimation. In: Balakrishnan, N., Rao, C.R. (Eds.), Handbook of Statistics, vol. 17. Elsevier, Amsterdam, pp. 337–377] and Chen et al. [2004. Ranked Set Sampling—Theory and Application. Lecture Notes in Statistics, vol. 176. Springer, New York] have provided excellent surveys of RSS and various inferential results based on RSS. In this paper, we use the idea of order statistics from independent and non-identically distributed (INID) random variables to propose ordered ranked set sampling (ORSS) and then develop optimal linear inference based on ORSS. We determine the best linear unbiased estimators based on ORSS (BLUE-ORSS) and show that they are more efficient than BLUE-RSS for the two-parameter exponential, normal and logistic distributions. Although this is not the case for the one-parameter exponential distribution, the relative efficiency of the BLUE-ORSS (to BLUE-RSS) is very close to 1. Furthermore, we compare both BLUE-ORSS and BLUE-RSS with the BLUE based on order statistics from a simple random sample (BLUE-OS). We show that BLUE-ORSS is uniformly better than BLUE-OS, while BLUE-RSS is not as efficient as BLUE-OS for small sample sizes (n<5$n<5$).     

Bayesian design in queues: An application to aeronautic maintenance

We exploit Bayesian criteria for designing M/M/c//r$M/M/c//r$ queueing systems with spares. For illustration of our approach we use a real problem from aeronautic maintenance, where the numbers of repair crews and spare planes must be sufficiently large to meet the necessary operational capacity. Bayesian guarantees for this to happen can be given using predictive or posterior distributions.     

Subset selection of superior populations when the number of populations is large

The situation where k populations are partitioned into one inferior group and one superior group is considered. The statistical problem is to select a random size subset of superior populations while trying to avoid including any inferior populations. A selection procedure is assumed to satisfy the condition that the probability of selecting at least one superior population is bounded below by P¹<1. The performance of a procedure is measured by the probability of including an inferior population.The asymptotic performance, as k→∞ of Gupta's traditional maximum type procedure ψ^G is considered in the location-model. For normally distributed populations, ψ^G turns out to be asymptotically optimal, provided the size of the inferior group does not become infinitely larger than the size of the superior group.     

An application of the Bernoulli part to local limit theorems for moving averages on stationary sequences

We consider partial sums S_n of a general class of stationary sequences of integer-valued random variables, and we provide sufficient conditions for S_n to satisfy a local limit theorem. To prove this result, we introduce a concept called the Bernoulli part. The amount of Bernoulli part in S_n determines the extent to which the density of S_n is relatively flat. If in addition S_n satisfies a global central limit theorem, the local limit theorem follows.