Economic Growth Sala I Martin Pdf

[Glendora Starr]

Akey economic issue is whether poor countries or regions tend to grow faster than rich ones: are there automatic forces that lead to convergence over time in levels of per capita income and product? After considering predictions of closed- and open-economy neoclassical growth theories, we examine data since 1840 from the U.S. states. We find clear evidence of convergence, but the findings can be reconciled quantitatively with neoclassical models only if diminishing returns to capital set in very slowly. The results from a broad sample of countries are similar if we hold constant a set of variables that proxy for differences in steady-state characteristics. Two types of existing theories seem to fit the facts: the neoclassical growth model with broadly-defined capital and a limited role for diminishing returns, and endogenous growth models with constant returns and gradual diffusion of technology across economies.

This graduate level text on economic growth surveys neoclassical and more recent growth theories, stressing their empirical implications and the relation of theory to data and evidence. The authors have undertaken a major revision for the long-awaited second edition of this widely used text, the first modern textbook devoted to growth theory. The book has been expanded in many areas and incorporates the latest research. After an introductory discussion of economic growth, the book examines neoclassical growth theories, from Solow-Swan in the 1950s and Cass-Koopmans in the 1960s to more recent refinements; this is followed by a discussion of extensions to the model, with expanded treatment in this edition of heterogenity of households. The book then turns to endogenous growth theory, discussing, among other topics, models of endogenous technological progress (with an expanded discussion in this edition of the role of outside competition in the growth process), technological diffusion, and an endogenous determination of labor supply and population. The authors then explain the essentials of growth accounting and apply this framework to endogenous growth models. The final chapters cover empirical analysis of regions and empirical evidence on economic growth for a broad panel of countries from 1960 to 2000. The updated treatment of cross-country growth regressions for this edition uses the new Summers-Heston data set on world income distribution compiled through 2000.

We see that the growth rate of bank loans has been very stable over time, hovering around 12-13 percent year over year, except during the financial crisis of 2008 and its immediate aftermath. Meanwhile, the rail freight growth series has shown a sustained decline over the past twelve years, reaching a low point in December 2015. This precipitous deceleration was one reason that market participants a year ago were so concerned that official statistics were not reflecting the true state of the Chinese economy. However, there are more innocuous explanations for the decline of rail freight growth, such as the structural transition of the Chinese economy from heavy industry toward services.

In light of the structural changes under way in the Chinese economy, we might devise a modified Li Keqiang index, placing more weight on the bank loans series than on the rail freight series (instead of weighting the three growth rate series equally). This approach would have sparked much less cause for concern at the end of 2015. But what weightings would be statistically sound? And, more fundamentally, how can we tell what the best set of weightings would be?

This hypothesis holds for a variety of possible interrelationships between true GDP growth and nighttime lights growth. In particular, as long as true GDP growth and nighttime lights growth are correlated, we can allow this correlation to change over time or vary across different areas of China. The correlation between official GDP growth and nighttime lights growth is documented in the scatter plot below. Our regression also includes flexible factors that absorb any nationwide changes in nighttime light intensity (or economic growth). For example, if Chinese lighting technology changed during the time period of our analysis, leading to a proportional brightening of all Chinese lights, the weightings we derive for the components of our new GDP growth proxy would not be affected.

We find that the components of the Li Keqiang index should not be assigned equal weighting, as is typically supposed. In fact, our analysis indicates that bank loan growth should be given six to eight times more weight than rail freight growth, with the optimal weighting on electricity production growth somewhere in between. Under additional assumptions (specifically, if we normalize our proxy to match the level and trend of official Chinese GDP growth before 2012), the implications of this reweighting on our optimal estimate of Chinese GDP growth are profound. We find that since 2012, our estimate of Chinese GDP growth was never appreciably lower, and was in many years higher, than the GDP growth rate reported in the official statistics. Adding other series besides those incorporated in the Li Keqiang index does not change our results.

The chart below presents the path of official Chinese GDP growth alongside our modified Li Keqiang index (with the weights determined by the nighttime lights regression). We place a 95 percent confidence interval around our prediction.

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Kent, eychenne: Thank you very much for your interest in our work. We are currently investigating employing this technique to look at economic activity in other countries, and look forward to posting results once we have them. Unfortunately, nighttime lights are a better indicator of economic growth in developing countries rather than in developed ones. In particular, until very recently, the satellites recording the lights had a maximum sensitivity that is close to the brightness of a typical developed-world city, which limited their ability to show lights brightening and dimming with developed country business cycles.

Andrew: Great question. In our analysis, we control for all general national trends in China, which should capture changes such as transitions to a different lighting technology. To alleviate the concern that such technology may be adopted differentially in more urban parts of China, we can also control for trends that vary by urbanization status, which does not affect our results.

excellent question as their population grows together with its GDP. There is a possibility for more job opportunities as their economy is growing rapidly fast. Because majority of the companies across the globe are relying on china to create their products.

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Xavier X. Sala i Martn[2] (also Sala-i-Martin in English) is an American economist and professor of economics at Columbia University. Sala i Martin is one of the leading economists in the field of economic growth.[3]

In addition to working at Columbia, he has been a professor at Yale University, Harvard University, and the Universitat Pompeu Fabra in Barcelona and the Barcelona Graduate School of Economics, where he usually visits for a term every summer.

Born in Cabrera de Mar, Catalonia, Sala i Martin earned a degree in economics from the Autonomous University of Barcelona in 1985. He completed his PhD in economics from Harvard University in 1990.[1]

Sala i Martin is one of the leading economists in the field of economic growth[3] and is consistently ranked among the most-cited economists in the world for works produced in the 1990s.[4][5] His works include the topics of economic growth, development in Africa, monetary economics, social security, health and economics, convergence, and classical liberal thinking, with his book Liberal Economics for Non-Economists and Non-Liberals.[6][7] The "liberal" in the title should be understood in the classic liberal/libertarian sense.

He has constructed an estimate of the world distribution of income,[8] which he has then used to estimate poverty rates and measures of inequality. The conclusions of this study offered a new point of view for two reasons. Firstly, the United Nations and the World Bank used to believe that although poverty rates were falling, the total number of poor people was increasing. He claimed that both were falling. Secondly, the United Nations and the World Bank believe that individual income inequalities were on the rise. He claimed that they were not.[9]

Sala i Martin and Elsa V. Artadi are the authors of the Global Competitiveness Index, used since 2004 for the Global Competitiveness Report, an index published by the World Economic Forum that ranks 142 countries by their level of economic competitiveness.[12][13]

He often collaborates with Catalan media to support the independence of Catalonia from Spain. In 2014 he had a public confrontation with Jos Manuel Barroso, the president of the European Commission, reproaching him the lack of support towards a democratic resolution of the conflict between Spain and Catalonia.[14]

He is a columnist for the Spanish newspaper La Vanguardia. He makes weekly appearances on the Catalan radio network RAC 1 and in the television show Divendres.[16][17][18][19][20][21] He also contributes to CNN.[22][23]

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