世界経済・社会統計 = World development indicators

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

The 2008 crash has left all the established economic doctrines - equilibrium models, real business cycles, disequilibria models - in disarray. Part of the problem is due to Smith’s "veil of ignorance": individuals unknowingly pursue society’s interest and, as a result, have no clue as to the macroeconomic effects of their actions: witness the Keynes and Leontief multipliers, the concept of value added, fiat money, Engel’s law and technical progress, to name but a few of the macrofoundations of microeconomics. A good viewpoint to take bearings anew lies in comparing the post-Great Depression institutions with those emerging from Thatcher and Reagan’s economic policies: deregulation, exogenous vs. endoge- nous money, shadow banking vs. Volcker’s Rule. Very simply, the banks, whose lending determined deposits after Roosevelt, and were a public service became private enterprises whose deposits determine lending. These underlay the great moderation preceding 2006, and the subsequent crash.

The Economic Institutions of Capitalism

1. Interaction. The interactions learners have with each other build interpersonal skills, such as listening, politely interrupting, expressing ideas, raising questions, disagreeing, paraphrasing, negotiating, and asking for help. 2. Interdependence. Learners must depend on one another to accomplish a common objective. Each group member has specific tasks to complete, and successful completion of each member’s tasks results in attaining the overall group objective.

将“Cooperative Learning”融入课堂——浅谈英语素质教育

This paper sets out to explore contexts for entrepreneurship, illustrating how a contextualized view of entrepreneurship contributes to our understanding of the phenomenon. There is growing recognition in entrepreneurship research that economic behavior can be better understood within its historical, temporal, institutional, spatial, and social contexts, as these contexts provide individuals with opportunities and set boundaries for their actions. Context can be an asset and a liability for the nature and extent of entrepreneurship, but entrepreneurship can also impact contexts. The paper argues that context is important for understanding when, how, and why entrepreneurship happens and who becomes involved. Exploring the multiplicity of contexts and their impact on entrepreneurship, it identifies challenges researchers face in contextualizing entrepreneurship theory and offers possible ways forward.

https://papers.ssrn.com/sol3/Delivery.cfm/j_1540-6520_2010_00427_x_wml.pdf?abstractid=1784106&mirid=2

Contextualizing Entrepreneurship—Conceptual Challenges and Ways Forward:

I. INTRODUCTION AND HISTORICAL BACKGROUND The Economic Freedom of the World (EFW) index was first produced by Gwartney. Block, and Lawson (1996) and has been updated annually since. (1) The EFW index has found a place as one of the top resources for academics. policy makers, and journalists who are looking for indicators on national economic policies around the world. Academically, the EFW index has been cited in hundreds of articles. Many. but not all, of these articles have a strong economic policy component to them and thus should be of interest to the readers of this journal. Here, we provide an accounting and description of this literature. The EFW index is designed to measure the consistency of a nation's policies and institutions with economic freedom. The EFW index places the concept of economic freedom within the classical liberal tradition that emphasizes the importance of private property, rule of law, free trade, sound money, and a limited role for government. Higher scores are accorded to nations with more secure property, freer trade, more stable money and prices, less government spending, and fewer regulations. The EFW index was conceived as a result of a 1984 Mont Pelerin Society meeting session in which George Orwell's book, 1984, was being discussed. (2) The question of the session was whether Orwell's dystopic depiction of the future had come true. Some discussants at the meeting thought Orwell was clearly wrong as democracy and human rights were well protected, at least in the Western nations that concerned Orwell. Others, most notably Michael Walker, the founder and then-Executive Director of Canada's Fraser Institute, countered that while that might be true of political and civil liberties, economic liberties are under increasing attack. According to Walker, economic life was becoming increasingly Orwellian. Further, he argued even our political and civil liberties were not out of the woods just yet. Walker quoted Milton Friedman, who wrote in Capitalism and Freedom (1962, p. 9): Historical evidence speaks with a single voice on the relation between political freedom and a free market. I know of no example in time or place of a society that has been marked by a large measure of political freedom, and that has not also used something comparable to a free market to organize the bulk of economic activity. Among the participants at this meeting was Milton Friedman himself, who noted that the debate on the floor about whether economic freedom was growing or eroding suffered from a critical lack of empirical data. The debaters employed little more than isolated anecdotes to make their points. As a result of this experience. Walker and Rose and Milton Friedman organized a meeting sponsored by Liberty Fund to discuss the prospects for creating some kind of measure of economic freedom. This first meeting ultimately led to a series of six meetings. The participants at these early meetings included a veritable Who's Who of classical-liberal scholars including Armen Alchian, Peter Bauer, Gary Becker, Arthur Denzau, Stephen Easton, David Friedman, John Goodman. Herb Grubel, Ronald Jones, Richard Rahn, Henri LePage, Henry Manne. Charles Murray, and Douglass North. At the fourth conference, held in Sea Ranch, California, Gwartney, Block, and Lawson (1992) presented a prototype index for 79 countries. The organizers briefly pursued the idea of doing a survey-based economic freedom index, but that effort failed, and they eventually asked Gwartney, Block, and Lawson to complete a publishable index. The index was finally released in 1996, 10 years after the original conference, as Economic Freedom of the World: 1975-1995. (3) Milton Friedman's "Foreword" in the first volume is worth reprinting here: Freedom is a big word, and economic freedom not much smaller. To talk about economic freedom is easy; to measure it, to make fine distinctions, assign numbers to its attributes. …

Economic freedom of the world: an accounting of the literature

The latest edition of this annual report, published in association with the Institute of Economic Affairs

Executive Summary: The index published in Economic Freedom of the World measures the degree to which the policies and institutions of countries are supportive of economic freedom. The cornerstones of economic freedom are personal choice, voluntary exchange, freedom to compete, and security of privately owned property. Forty-two data points are used to construct a summary index and to measure the degree of economic freedom in five broad areas:

Size of Government: Expenditures, Taxes, and Enterprises;

Legal Structure and Security of Property Rights;

Access to Sound Money;

Freedom to Trade Internationally;

Regulation of Credit, Labor, and Business.


Economic freedom has suffered another setback

The chain-linked summary index (exhibit 1.4) permits comparisons over time. The average economic freedom score rose from 5.53 (out of 10) in 1980 to 6.74 in 2007, but fell back to 6.67 in 2008, and to 6.64 in 2009, the most recent year for which data are available. (See chapter 1 for a discussion.)

In this year’s index, Hong Kong retains the highest rating for economic freedom, 9.01 out of 10. The other na- tions among the top 10 are: Singapore (8.68); New Zealand (8.20); Switzerland (8.03); Australia (7.98); Canada (7.81); Chile (7.77); United Kingdom (7.71); Mauritius (7.67); and the United States (7.60).

The rankings (and scores) of other large economies are Germany, 21 (7.45); Japan, 22 (7.44); France, 42 (7.16); Italy, 70 (6.81); Mexico, 75 (6.74); Russia, 81 (6.55); China, 92 (6.43); India, 94 (6.40); and Brazil, 102 (6.19).

The bottom 10 nations are: Zimbabwe (4.08); Myanmar (4.16); Venezuela (4.28); Angola (4.76); Democratic Republic of Congo (4.84); Central African Republic (4.88); Guinea-Bissau (5.03); Republic of Congo (5.04); Burundi (5.12); and Chad (5.32).


The world’s largest economy, the United States, has suffered one of the largest declines in economic freedom over the last 10 years, pushing it into tenth place. Much of this decline is a result of higher government spending and borrowing and lower scores for the legal structure and property rights components. Over the longer term, the summary chain- linked ratings of Venezuela, Zimbabwe, United States, and Malaysia fell by eight-tenths of a point or more between 1990 and 2009, causing their rankings to slip.

The chain-linked summary ratings of Uganda, Zambia, Nicaragua, Albania, and Peru have increased by three or more points since 1990. The summary ratings of eight other countries—Bulgaria, Poland, El Salvador, Romania, Ghana, Nigeria, Hungary, and Guinea-Bissau—increased by between two and three points during this same period.

Nations that are economically free out-perform non-free nations in indicators of well-being

Nations in the top quartile of economic freedom had an average per-capita GDP of $31,501 in 2009, compared to $4,545 for those nations in the bottom quartile, in constant 2005 international dollars.

Nations in the top quartile of economic freedom had an average growth in per-capita GDP between 1990 and 2009 of 3.07%, compared to 1.18% for those nations in the bottom quartile, in constant 2005 international dollars (exhibit 1.10).

In the top quartile, the average income of the poorest 10% of the population was $8,735, compared to $1,061 for those in the bottom quartile, in constant 2005 international dollars (exhibit 1.12). Interestingly, the aver- age income of the poorest 10% in the top quartile is almost double the overall income per capita in the bot- tom quartile ($4,545, exhibit 1.9): the poorest people in the most economically free countries are nearly twice as rich as the average people in the least free countries.

Life expectancy is 79.4 years in the top quartile compared to 60.7 years in the bottom quartile (exhibit 1.13).

The $1.25-per-day poverty rate is 2.7% in the top quartile compared to 41.5% in the bottom quartile (exhibit 1.17).

http://edoc.vifapol.de/opus/volltexte/2012/3533/pdf/EFR_2011.pdf

Economic Freedom of the World: 2011 Annual Report

Executive Summary:

Economic Freedom of the World

The index published in Economic Freedom of the World measures the degree to which the policies and institutions of countries are supportive of economic freedom. The cornerstones of economic freedom are personal choice, voluntary exchange, free- dom to compete, and security of privately owned property. Forty-two variables are used to construct a summary index and to measure the degree of economic freedom in five broad areas:

1 Size of Government;

2 Legal System and Property Rights;

3 Sound Money;

4 Freedom to Trade Internationally;

5 Regulation.


Since our first publication in 1996, numerous studies have used the data pub- lished in Economic Freedom of the World to examine the impact of economic free- dom on investment, economic growth, income levels, and poverty rates. Virtually without exception, these studies have found that countries with institutions and policies more consistent with economic freedom have higher investment rates, more rapid economic growth, higher income levels, and a more rapid reduction in poverty rates.

The EFW index now covers 152 countries and territories. Data are available for approximately 100 nations and territories back to 1980, and many back to 1970.3 This data set makes it possible for scholars to analyze the impact of both cross-coun- try differences in economic freedom and changes in that freedom across a three- decade time frame.

Economic freedom from around the world

Average chain-linked rating

The average chain-linked economic freedom rating for the 101 countries with rat- ings since 1980 has increased from 5.34 in 1980 to 5.82 in 1990 to 6.74 in 2000 and finally to 6.87 in 2011. After a global average drop between 2007 and 2009, the aver- age summary rating increased modestly in both 2010 and 2011, though it remains below its peak level of 6.92 in 2007. The chain-linked index is used for this compari- son because it is most appropriate for measurement of changes across time.

Countries included

There are 152 countries included in this year’s index, up from 144 last year. The new countries added to the index (with data for both 2010 and 2011) are Brunei Darussalam, Cape Verde, The Gambia, Lebanon, Suriname, Swaziland, Tajikistan, Timor-Leste, and Yemen. Because of the civil war and the unreliability of the data since 2011, the rating for Syria has been temporarily suspended, though historical data are included in Chapter 2: Country Data Tables.

Top-rated countries

Hong Kong and Singapore, once again, occupy the top two positions. The other nations in the top ten are New Zealand, Switzerland, United Arab Emirates, Mauritius, Finland, Bahrain, Canada, and Australia.

Other major countries

The rankings of some other major countries are: United Kingdom (12th), United States (17th), Germany (19th), Japan (33rd), South Korea (33rd), France (40th), Italy (83rd), Mexico (94th), Russia (101st), Brazil (102nd), India (111th), and China (123rd).

Lowest-rated countries

The ten lowest-rated countries are: Algeria, Democratic Republic of Congo, Burundi, Central African Republic, Angola, Chad, Zimbabwe, Republic of Congo, Myanmar, and, in last place, Venezuela. Eight of the countries in the bottom ten are located in Africa.

Nations that are economically free out-perform non-free nations in indicators of well-being

Nations in the top quartile of economic freedom had an average per-capita GDP of $36,446 in 2011, compared to $4,382 for nations in the bottom quartile in 2011US(PPP) dollars (Exhibit 1.6).

In the top quartile, the average income of the poorest 10% was $10,556, compared to $932 in the bottom quartile in 2011US(PPP) dollars (Exhibit 1.9). Interestingly, the average income of the poorest 10% in the most economically free nations is more than twice the overall average income in the least free nations.

Life expectancy is 79.2 years in nations in the top quartile compared to 60.2 years in those in the bottom quartile (Exhibit 1.10).

Political and civill iberties are considerably higher in economically free nations than in unfree nations (Exhibit 1.11).

Economic Freedom of the World: 2013 Annual Report

(ProQuest: ... denotes formula omitted.)IntroductionThe question of why some areas are rich and some are poor has been at the center of economics since Adam Smith ([1776] 1998) first published his Inquiry into the Nature and Causes of the Wealth of Nations. In his analysis, Smith focused the division of labor and how the division of labor was limited by the size (or 'extent' as he termed it) of the market. Larger markets lead to an increase in the division of labor and thus higher productivity. Higher productivity, in turn, leads to economic progress directly by increasing wages and indirectly through freeing up scarce resources for other uses.Ricardo (1817), however, focused attention back on the role that inputs such as land, labor, and capital played in economic growth. The creation of macroeconomic statistics in the early twentieth century led economists to focus on aggregate theories of growth that could explain this newly developed macroeconomic data. Solow (1956) developed a simple growth model where economic output was simply a mathematical function of capital and labor inputs [Y =/(K,L)] based on neoclassical theory that, when tested empirically, fit the available U.S. data quite well. The Solow model was the dominant theory of economic growth from the time of its creation until the 1980s and is still heavily used in many graduate macroeconomics classes. While this model has been augmented to sometimes include measures of technology and human capital quality, it fundamentally ignores the institutional arguments made by Adam Smith. In the Solow growth model, these complex institutional structures are simply represented by the functional form of the model, f(*).During the 1980s new data sets were created that contained macroeconomic data on a large number of countries over an extended period of time (see, for example, Summers and Heston (1991)). The creation of these data sets allowed economists for the first time to test whether per-capita incomes across countries were converging to equality-a key prediction of the neoclassical growth model (Romer, 1994). Subsequent research on the question of convergence has shown that there is no clear tendency for poor regions to grow faster than wealthier regions (Romer, 1994) although some research does show that regions within a country do converge, albeit slowly (Barro and Sala-i-Martin, 1992; Holtz-Eakin, 1993). At best, convergence is a slow and discontinuous process (Martin and Sunley, 1998). The finding that convergence sometimes happens slowly within a country (or a set of similar countries) has led to the idea of conditional convergence, where convergence happens conditional on regions having similar properties.The failure to find convergence in cross-country regressions was problematic since the Solow model was the model of economic growth at the time and had a strong influence on public policy.9 It could not, however, explain key features of the real world, such as persistent differences in income levels across countries. Neoclassical growth theory could also not explain the relationship between entrepreneurship and economic growth since the level of innovation was determined exogenous to the system. Even models like Barro and Sala-i-Martin's (1992) that relax the neoclassical assumption of uniform technology across space have no explanation for why technological innovation might vary from place to place. Out of this disenchantment came endogenous growth theory, which relaxed the neoclassical assumption of exogenous technological change and the non-excludability of technology.Unfortunately, endogenous growth theory cannot explain divergent levels of income across countries or the rapid development of countries like South Korea (Parente, 2001). From the standpoint of public policy, the failure of endogenous growth models to provide an explanation for varying levels of economic development is troubling because the sources of growth in endogenous growth models (such as the percentage of GDP spent on research and development) may not be the route to development. …

Institutions, Entrepreneurship, and Regional Differences in Economic Growth1

The international development community has encouraged investment in physical and human capital as a precursor to economic progress. Recent evidence shows, however, that increases in capital do not always lead to increases in output. We develop a growth model where the allocation and productivity of capital depends on a country's institutions. We find that increases in physical and human capital lead to output growth only in countries with good institutions. In countries with bad institutions, increases in capital lead to negative growth rates because additions to the capital stock tend to be employed in rent-seeking and other socially unproductive activities.

Joshua C. Hall

Papers

Economic freedom of the world: an accounting of the literature

Economic Freedom of the World: 2011 Annual Report

Economic Freedom of the World: 2013 Annual Report

Institutions, Entrepreneurship, and Regional Differences in Economic Growth1

Institutions, Capital, and Growth