This article examines the relationship between intergroup threat and negative outgroup attitudes. We first qualitatively review the intergroup threat literature, describing the shift from competing theories toward more integrated approaches, such as the integrated threat theory (ITT; W. G. Stephan & Stephan, 2000). The types of threats discussed include: realistic threat, symbolic threat, intergroup anxiety, negative stereotypes, group esteem threat, and distinctiveness threat. We then conducted a quantitative meta-analysis examining the relationships between various intergroup threats and outgroup attitudes. The meta-analysis, involving 95 samples, revealed that 5 different threat types had a positive relationship with negative outgroup attitudes. Additionally, outgroup status moderated some of these relationships. Implications and future directions are considered.

Intergroup Threat and Outgroup Attitudes: A Meta-Analytic Review

A comprehensive account of economic size distributions around the world and throughout the years In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences. Statistical Size Distributions in Economics and Actuarial Sciences is the first collection to systematically investigate a wide variety of parametric models that deal with income, wealth, and related notions. Christian Kleiber and Samuel Kotz survey, compliment, compare, and unify all of the disparate models of income distribution, highlighting at times a lack of coordination between them that can result in unnecessary duplication. Considering models from eight languages and all continents, the authors discuss the social and economic implications of each as well as distributions of size of loss in actuarial applications. Specific models covered include: Pareto distributions Lognormal distributions Gamma-type size distributions Beta-type size distributions Miscellaneous size distributions Three appendices provide brief biographies of some of the leading players along with the basic properties of each of the distributions. Actuaries, economists, market researchers, social scientists, and physicists interested in econophysics will find Statistical Size Distributions in Economics and Actuarial Sciences to be a truly one-of-a-kind addition to the professional literature.

Statistical Size Distributions in Economics and Actuarial Sciences

The modern literature on the economics of immigration focuses on 3 related issues: 1) what determines the size and skill composition of immigrants flows to any particular host country; 2) how do the immigrants adapt to the host countrys economy; and 3) what is the impact of immigrants on the host countrys economy? This article reviews the theoretical framework and empirical evidence provided by the economics literature on these questions. It demonstrates that the economic approach using the assumption that migration behavior is guided by the search for better economic opportunities and that the exchanges among the various players are regulated by an immigration market leads to substantial insights in to these issues. (authors)

Economic theory and international migration.

The Price of Inequality: How Today's Divided Society Endangers Our Future. Joseph E. Stiglitz, 414 pages, New York: W. W. Norton & Company, 2012.I LOVE THESE GUYS''(Joseph Stiglitz) is an insanely great economist,'' so writes Paul R. Krugman, who should know. These two like to write books for the populace at large on the topic of macroeconomics. Krugman also likes to spout offon Sunday news shows like ''Meet the Press,'' and on all the cable news programs. You can see Krugman arguing with Bill O'Reilly on Meet the Press. From YouTube: ''Don't call me a liar, pal, that's what you do all the time,'' says O'Reilly; ''This is not your show, so you can't cut offmy mic,'' says Krugman. Judging by their expressions, I was glad Tim Russert (6- 3-) was there in the studio at the time to protect Krugman (5- 7-) (O'Reilly stands 6- 4-). Conservative pundits dislike both economists, but pretty much leave Stiglitz alone.Krugman makes it a point to stay out of government affairs. Stiglitz does just the opposite, and he sometimes gets burned. Stiglitz was part of Bill Clinton's Council of Economic Advisers and was Chief Economist for the World Bank. After much criticism of the way the International Monetary Fund (IMF) conducted lending to developing countries, he was pretty much fired from the World Bank. Comparing the two, you would have to say that Stiglitz is more the bleeding heart, while Krugman says that what he dislikes most is the dishonesty he sees in political-economic discourse. Both are champions of the common man.Since Stiglitz can make the very valid claim for being ''an insanely great economist,'' most everything he says in his books should be taken seriously. There are some real gems in this book. I especially like the perspective he lends to some of the more peculiar things that happened before, during, and after the financial crisis. People hear about these things in the news from some announcer who makes them sound like just more news-bites, but they are, after all, unprecedented (and largely absurd). Take ''robo-signing'' for instance (page 198).WHAT GOES FOR NEWSRobo-signing was part of what happened during the foreclosure process after the massive numbers of defaults of subprime mortgages. Big banks intentionally did not follow mandated law. Apart from ignoring debtors' rights, an ensuing mess followed. Robo-signing was nothing less than a blatant attempt at rewriting property law, and resulted in lying to the courts about the state of each property's title, literally hundreds of times. No bank officer was charged with a crime. By contrast, the savings and loan crisis of the 1980s led to 829 individual convictions and 650 prison sentences. Nowadays the big banks just pay fines as part of settlements where they admit no guilt, and it's just part of doing business.Take algorithmic or ''flash'' trading in the stock exchanges (page 164). These are buys and sales made in nanoseconds on the basis of extracting information from the patterns of prices and trades. Nothing like real information gathered through market research on an industry, or on a firm in a certain industry, backs up these trades. But traders swear that ''price discovery'' is happening this way, and that all this backs up the efficient markets model. So on May 6, 2010 stock prices plummeted to a point where the Dow Jones temporarily lost 10% of its value. There are reasons to believe that these trades ''make markets not just more volatile but also less 'informative' '' (page 166). Still, the talk on the street is all about efficient markets (echoing Alan Greenspan's failures at the Federal Reserve).Take failed privatizations. When electric power in California was liberalized and Enron manipulated prices and public power to its advantage, this was a story about the company's accounting practices, not about privatizing something that had no business being privatized. …

The Price of Inequality: How Today's Divided Society Endangers Our Future

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality or social welfare is greater in one distribution than in another for general classes of indices. We also derive the sampling distribution of the maximal poverty lines (or income censoring thresholds) up to which we may confidently assert that poverty or social welfare is greater in one distribution than in another. The sampling distribution of convenient estimators for dual approaches to the measurement of poverty is also established. The statistical results are established for deterministic or stochastic poverty lines as well as for paired or independent samples of incomes. Our results are briefly illustrated using data for 6 countries drawn from the Luxembourg Income Study data bases.

Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality

The widely used Cochrane-Orcutt and Hildreth-Lu procedures for estimating the parameters of a linear regression model with first-order autocorrelation typically ignore the first observation. An alternative maximum likelihood procedure which incorporates the first observation and the stationarity condition of the error process is proposed in this paper. It is similar to the Cochrane-Orcutt procedure, and appears to be at least as computationally efficient. This estimator is superior to the conventional ones on theoretical grounds, and sampling experiments suggest that it may yield substantially better estimates in some circumstances.

A maximum likelihood procedure for regression with autocorrelated errors

The paper considers the problem of statistical inference with estimated Lorenz curves and income shares. The full variance-covariance structure of the (asymptotic) normal distribution of a vector of Lorenz curve ordinates is derived and shown to depend only on conditional first and second moments that can be estimated consistently without prior specification of the population density underlying the sample data. Lorenz curves and income shares can thus be used as tools for statistical inference instead of simply as descriptive statistics.

https://www.jstor.org/stable/pdfplus/2297772.pdf

Distribution-Free Statistical Inference with Lorenz Curves and Income Shares

This paper examines whether there is a "double-negative' effect on the earnings of immigrant women arising from a possible combined negative impact of gender and birthplace on earnings. The paper finds that a double-negative effect on earnings does not appear to hold across the board for all immigrant women, but is quite marked for highly educated women; and that a conventionally estimated rate of earnings adjustment for immigrant women appears much less than that for men and is not at all statistically significant, so that any initial earnings gap relative to native-born women changes very little over the worker's career. -Authors

Is There a Double-Negative Effect on the Earnings of Immigrant Women?

In a recent paper, Beach and Davidson [1983] extended the principles of statistical inference to Lorenz curves and income shares by establishing the (asymptotic) distribution and covariance structure of a vector of Lorenz curve ordinates corresponding to a set of quantile abscissae. One can thus use the Lorenz curve and income shares, no longer just as descriptive devices for summarizing distribution information, but now also as analytical tools for comparing alternative distributions and carrying out conventional statistical inference on them. It would clearly be desirable, however, to extend and complement this work by providing a method for computing a set of joint confidence intervals about these income shares and for illustrating graphically a joint confidence band about a set of estimated Lorenz curve ordinates. The present paper provides a new and simple technique for doing this. When analyzing differences between sets of income shares or Lorenz curves, one typically wants to elicit more detailed information than is provided by a standard joint chi-square test on the overall set of shares. That is, when the hypothesis of two sets of shares being the same is rejected, we generally want to know further which particular differences in shares are different from zero, and of these nonzero differences which are positive and which negative (Savin [1980]). A natural way of providing such information is through multiple comparison procedures developed in this paper. In a recent work, Richmond [1982] has developed a general method of finding multiple comparison intervals that is particularly suited to the present problem and in this situation appears to dominate other conventional alternatives. In contrast, for example, to Scheff&'s S-projection method, Richmond's approach focuses on a set of primary points of interest (income shares) among a more general set of points (including the Lorenz curve ordinates) and optimizes the joint confidence interval lengths on this primary set of points. Since estimated Lorenz curve ordinates are built up from underlying income shares, these shares (perhaps further supplemented) are natural choices for the primary set. The method, however, also provides a joint confidence band that geometrically bounds the set of Lorenz curve ordinates (and interpolated segments between them). The present

Joint Confidence Intervals for Income Shares and Lorenz Curves

Since 9/11 there have been many changes to the external environment of Canadian immigration, a number of criticisms of current immigration policy in Canada, and several proposals for dealing with current labour market needs and settlement patterns of immigrants to Canada. In "Canadian Immigration Policy for the 21st Century" authors examine the issues raised by these concerns.The topics covered include international context and immigration policy goals, the role of immigration in meeting Canada's demographic and labour market needs, decentralization of immigration policy with special focus on the Quebec perspective and the recent Manitoba experience, policy responses to increasing international labour mobility, immigration data resources in Canada, the changing immigrant experience in the labour market including issues of skill recognition and the effects of business cycles on labour market integration, and social inclusion of immigrants, including the health of immigrant children and visible minority enclaves in major Canadian cities.The contributors include: Michael Abbott (Queen's University), Naomi Alboim (Queen's University), Roderic Beaujot (University of Western Ontario), David Card (University of California at Berkeley), Barry Chiswick (University of Illinois at Chicago), Gerry Clement (Manitoba Labour and Immigration Department), Don DeVoretz (Simon Fraser University), Erwin Diewert (University of British Columbia), Victoria Esses (University of Western Ontario), Alan Green (Queen's University), Gilles Grenier (University of Ottawa), and, Violet Kaspar (University of Toronto). It also includes: Ted McDonald (University of New Brunswick), Alice Nakamura (University of Alberta), Masao Nakamura (University of British Columbia), Doug Norris (Statistics Canada), Garnett Picott (Statistics Canada), Jeffrey Reitz (University of Toronto), Craig Riddell (University of British Columbia), Janice Stein (University of Toronto), Arthur Sweetman (Queen's University), Yvan Turcotte (Ministere des Relations avec les Citoyens et de l'Immigration), and Chris Worswick (Carleton University).

Charles M. Beach

Papers

A maximum likelihood procedure for regression with autocorrelated errors

Distribution-Free Statistical Inference with Lorenz Curves and Income Shares

Is There a Double-Negative Effect on the Earnings of Immigrant Women?

Joint Confidence Intervals for Income Shares and Lorenz Curves

Canadian Immigration Policy for the 21st Century