We investigate whether income inequality affects subsequent growth in a cross-country sample for 1965-90, using the models of Barro (1997), Bleaney and Nishiyama (2002) and Sachs and Warner (1997), with negative results. We then investigate the evolution of income inequality over the same period and its correlation with growth. The dominating feature is inequality convergence across countries. This convergence has been significantly faster amongst developed countries. Growth does not appear to influence the evolution of inequality over time. Outline

https://www.econstor.eu/bitstream/10419/81822/1/02-28.pdf

Economic growth and income inequality

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

This paper reports trends in educational assortative marriage from 1940 to 2003 in the U.S. Analyses of Census and Current Population Survey data show that educational homogamy increased over most of this period, although there is some evidence of stabilization in the 1990s. From 1940 to the early-1970s, these increases were generated by decreasing intermarriage among groups of relatively well educated persons. Beginning in the early-1970s, the odds of intermarriage among the highly educated stabilized while the odds that high school dropouts marry up dropped substantially. These trends are similar for a broad cross-section of married couples and for newlyweds.

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Trends in Educational Assortative Marriage From 1940 to 2003 - eScholarship

Examples are discussed to show the differences among discriminant analysis, logistic regression, and multiple regression. Chapter 6, “Multivariate Analysis of Variance,” presents advantages of multivariate analysis of variance (MANOVA) over univariate analysis of variance (ANOVA), discusses assumptions of MANOVA, and assesses validations of MANOVA assumptions and model estimation. The authors also discuss post hoc tests of MANOVA and multivariate analysis of covariance. Chapter 7, “Conjoint Analysis,” explains what conjoint analysis does and how it is different from other multivariate techniques. Guidelines of selecting attributes, models, and methods of data collection are presented. Chapter 8, “Cluster Analysis,” studies objectives, roles, and limitations of cluster analysis. Two basic concepts: similarity and distance are discussed. The authors also discuss details of five most popular hierarchical algorithms (singlelinkage, complete-linkage, average-linkage, centroid method, Ward’s method) and three nonhierarchical algorithms (the sequential threshold method, the parallel threshold method, and the optimizing procedure). Profiles of clusters and guidelines for cluster validation are studied as well. Chapter 9, “Multidimensional Scaling and Correspondence Analysis,” introduces two interdependence techniques to display the relationships in the data. The book describes clearly and intuitively the differences between the two techniques and how these two techniques are performed. Chapters 10–12 cover topics in SEM. Chapter 10, “Structural Equation Modeling: An Introduction,” introduces SEM and related concepts such as exogenous, endogenous constructs, and so on, points out the differences between SEM and other multivariate techniques, overviews the decision process of SEM. Chapter 11, “Confirmatory Factor Analysis,” explains the differences between exploratory and confirmatory factor analysis, discusses how to construct, validate, and assess the goodness of fit of a measurement model in SEM by confirmatory factor analysis. Chapter 12, “Testing a Structural Model,” presents some methods of SEM in examining the relationships between latent constructs. The book is an excellent book for people in management and marketing. For the Technometrics audience, this book does not have much flavor of physical, chemical, and engineering sciences. For example, partial least squares, a very popular method in Chemometrics, is discussed but not as detailed as other techniques in the book. Furthermore, due to the amount of materials covered in the book, it might be inappropriate for someone who is new to multivariate analysis.

The Grammar of Graphics

The Atlas of Economic Complexity: Mapping Paths to Prosperity

Long-term exposure to ambient air pollutant concentrations is known to cause chronic lung inflammation, a condition that may promote increased severity of COVID-19 syndrome caused by the novel coronavirus (SARS-CoV-2). In this paper, we empirically investigate the ecologic association between long-term concentrations of area-level fine particulate matter (PM2.5) and excess deaths in the first quarter of 2020 in municipalities of Northern Italy. The study accounts for potentially spatial confounding factors related to urbanization that may have influenced the spreading of SARS-CoV-2 and related COVID-19 mortality. Our epidemiological analysis uses geographical information (e.g., municipalities) and negative binomial regression to assess whether both ambient PM2.5 concentration and excess mortality have a similar spatial distribution. Our analysis suggests a positive association of ambient PM2.5 concentration on excess mortality in Northern Italy related to the COVID-19 epidemic. Our estimates suggest that a one-unit increase in PM2.5 concentration (µg/m3) is associated with a 9% (95% confidence interval: 6-12%) increase in COVID-19 related mortality.

/pdf/the-effects-of-air-pollution-on-covid-19-related-mortality-3k0lm0q3ty.pdf

The Effects of Air Pollution on COVID-19 Related Mortality in Northern Italy.

The 2007–2008 global recession and consequent slow recovery have revealed considerable heterogeneity in economic performance across countries and regions. This study contributes innovatively to existing resilience literature by identifying a life cycle resilience framework and computing a “handy” composite Regional Economic Resilience Indicator. We analyse economic resilience by means of a cluster and exploratory spatial data analysis, revealing well-defined spatial patterns in the EU. National resilience trends dominate in the EU-15, while a more heterogeneous spatial pattern is present in the EU-13. Our findings can support the monitoring of economic resilience at regional level and facilitate a common understanding of this complex and dynamic process for policy purposes.

A composite policy tool to measure territorial resilience capacity

Land consumption and income in Ecuador: A case of an inverted environmental Kuznets curve.

Analysing Domestic Tourism Flows at the Provincial Level in Spain by Using Spatial Gravity Models

In this study, we identify some individual and contextual factors potentially affecting subjective well-being in developing countries and check their effect in the Ecuadorian case. Ecuador is an oil country where attempts have been made to overcome deep social and territorial inequalities by placing human well-being at the core of public policy through the National Plan for Good Living. By means of ordinary least squares and ordered logit with clustered standard errors, as well as multilevel ordered logit models, we find that oil-dependent territories negatively affect well-being. Moreover, women and indigenous people report lower well-being, while personal income, education, housing quality, institutional trust, health insurance and social relationships can improve it. From a policy perspective, we find that basic unmet needs still need to be fulfilled to increase well-being, and further improvements of the institutional framework, redistributive system and inclusion policies are required. In this respect, we observe that Good Living-based policy accurately addresses these elements and, therefore, has great potential for application in other countries with similar characteristics.

/pdf/the-determinants-of-subjective-well-being-in-a-developing-1nnetgq41g.pdf

Nicola Pontarollo

Papers

The Effects of Air Pollution on COVID-19 Related Mortality in Northern Italy.

A composite policy tool to measure territorial resilience capacity

Land consumption and income in Ecuador: A case of an inverted environmental Kuznets curve.

Analysing Domestic Tourism Flows at the Provincial Level in Spain by Using Spatial Gravity Models

The Determinants of Subjective Well-Being in a Developing Country: The Ecuadorian Case