scholarly journals Demographic Cycles and Economic Growth: The Long Swing Reconsidered

1969 ◽  
Vol 29 (4) ◽  
pp. 633-656 ◽  
Author(s):  
Allen C. Kelley
Keyword(s):  
Economic Growth ◽  
Growth Rates ◽  
Secular Trend ◽  
Equal Distribution ◽  
Aggregate Production ◽  
Price Series ◽  
History Of ◽  
Per Capita ◽  
The Business Cycle ◽  
Capita Output

For many Western countries the history of the last two centuries reveals both a sustained rise in per capita output and a tendency toward a more equal distribution of the economic product. The experience has been characterized, however, by repetitive fluctuations in the levels and growth rates of aggregate production and its components. The length of the shorter of these fluctuations, the business cycle, ranges from the 40- to 45-month inventory cycle to the so-called Juglar of seven to ten years. Two other classes of interruptions in the secular trend have also been singled out for study by economic historians. The first is the Kondratieff cycle, a movement of roughly fifty years which has been primarily identified in price series. The second is the Kuznets cycle, or “long swing,” which in length is between the Juglar and the Kondratieff. The long swing constitutes the primary theme of this study.

scholarly journals Examining GDP Growth and Its Volatility: An Episodic Approach

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 890
Author(s):  
Jakub Bartak ◽  
Łukasz Jabłoński ◽  
Agnieszka Jastrzębska
Keyword(s):  
Economic Growth ◽  
Genetic Algorithm ◽  
Time Series ◽  
Human Capital ◽  
Growth Rates ◽  
Structural Breaks ◽  
Negative Relationship ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Per Capita

In this paper, we study economic growth and its volatility from an episodic perspective. We first demonstrate the ability of the genetic algorithm to detect shifts in the volatility and levels of a given time series. Having shown that it works well, we then use it to detect structural breaks that segment the GDP per capita time series into episodes characterized by different means and volatility of growth rates. We further investigate whether a volatile economy is likely to grow more slowly and analyze the determinants of high/low growth with high/low volatility patterns. The main results indicate a negative relationship between volatility and growth. Moreover, the results suggest that international trade simultaneously promotes growth and increases volatility, human capital promotes growth and stability, and financial development reduces volatility and negatively correlates with growth.

scholarly journals Economic Development

2019 ◽  
Author(s):  
Dhina Vadyza
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Income Distribution ◽  
Urban Areas ◽  
Gini Index ◽  
Production Factor ◽  
Real Economy ◽  
Long Run ◽  
Per Capita ◽  
Capita Output

Economic growth is a process of increasing per capita output that occurs continuously in the long run. Economic growth is one indicator of the success of development. Increasingly increasing economic growth usually increases people's welfare. While economic development is an effort to increase per capita income by processing potential economic forces into the real economy through investment, increasing knowledge, increasing skills, using technology, adding management skills and organizing.Economic growth is also related to the increase in "per capita output". The theory must include theories about GDP growth and theories about population growth. Then the third aspect is economic growth in a long-term perspective, that is, if for a long period of time the per capita output shows an increasing tendency.The distribution of income distribution in Indonesia is increasingly uneven. This can be seen from the increasing Indonesian Gini Index. As is known, the Gini index measures the income distribution of a country. The size of the Gini index Between 0 (zero) to 1 (one), the Gini index Equal to 0 (zero) indicates the index that the income distribution is perfectly equal, while the Gini index is 1 (one ) shows that the income distribution is totally uneven. Based on the data, the Indonesian Gini index continues to increase from year to year.The state of income distribution in Indonesia since 1970 can be said not to improve, this is caused by many factors, including the First production factor market (input market) which is the increase in labor supply which results in excess labor, low labor wages and limited employment opportunities in urban areas resulting in unemployment and urban slums.Second, land ownership. Land distribution is the main determinant of the extent of poverty and income distribution.

A Comparison of the Economic Growth of the Baltic States between the Two World Wars

2016 ◽  
Vol 12 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Zenonas Norkus
Keyword(s):  
Economic Growth ◽  
Gross Domestic Product ◽  
Growth Rates ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Economic Output ◽  
Measurement Units ◽  
Per Capita ◽  
Cross Country ◽  
The Baltic

AbstractThis paper contributes to cliometric research on the economic output of Finland, Estonia, Lithuania and Latvia between 1913 and 1938. For Finland, gross domestic product (GDP) values from Maddison project dataset are accepted. For Estonia, Arno Köörna’s and Jaak Valge’s estimates are endorsed with reservations for 1923–1924. According to an optimistic estimate, Lithuania’s GDP per capita was below all-Russian mean in 1913, but was not less than USSR level in 1938, while Gediminas Vaskela’s pessimistic estimate of the 1938 Lithuanian GDP implies its GDP growth underperformance. Using new sources, the first estimates of Latvia’s output for the 1913–1938 period in cross-country and cross-temporally comparable measurement units (1990 Geary Khamis international $) are substantiated. Under optimistic estimates of Lithuanian GDP growth, this country was on par with Finland in terms of annual growth rates, with Latvia following next and Estonia displaying the weakest growth performance.

The Uruguayan Economy: Its Basic Nature and Current Problems

1965 ◽  
Vol 7 (3) ◽  
pp. 316-330 ◽  
Author(s):  
Herman E. Daly
Keyword(s):  
Economic Growth ◽  
South America ◽  
Economic Activity ◽  
Economic History ◽  
Gross National Product ◽  
Turn Of The Century ◽  
Economic Dimension ◽  
History Of ◽  
Per Capita ◽  
The Welfare State

The economic history of Uruguay from the turn of the century up to the early 1950's is characterized by economic growth, by extensive governmental involvement in economic activity, and by an ardent secularist faith in the welfare state ideals of the great José Batlle y Ordóñez and the Batllista tradition which lived on after him. Its small size, stable democracy, and apparent aloofness from the problems of the rest of the continent have earned la Republica Oriental del Uruguay such sobriquets as the “Switzerland” or “Utopia” of South America. Beginning in the early 1950's, however, there were signs that this country which had for so long been a model laboratory for progress and reform to its crisis-ridden neighbors, was itself about to face a crisis. The economic dimension of the Uruguayan crisis is that the annual per capita gross national product (currently about 500 dollars) has not risen for over a decade, and has in fact declined slightly in the last several years.

Decomposition of Russian GDP growth rates in 2007—2017 and forecast for 2018—2020

2018 ◽  
pp. 5-31 ◽  
Author(s):  
S. M. Drobyshevsky ◽  
G. I. Idrisov ◽  
A. S. Kaukin ◽  
P. N. Pavlov ◽  
S. G. Sinelnikov‑Murylev
Keyword(s):  
Economic Growth ◽  
Growth Rates ◽  
Gdp Growth ◽  
Structural Reforms ◽  
Structural Unemployment ◽  
Russian Economy ◽  
The Business Cycle ◽  
Random Shocks ◽  
Economic Growth Rates ◽  
Further Development

The paper provides further development of the methodology of GDP growth rates decomposition, adapted for the case of Russia. It proposes the calculation of indicators of structural unemployment NAWRU and total factor productivity for the Russian economy. The paper offers estimates of structural, foreign trade and market components of GDP growth rates for various macroeconomic scenarios for 2018—2020. The sum of the components of the business cycle and random shocks is expected to be the main source of Russian GDP growth in 2018—2020, which together with the renewal of investment in 2017 may indicate the beginning of a new cycle of economic growth in Russia. Within the framework of the considered macroeconomic scenarios an expected contribution of the terms of trade component will be of an order of –1 p. p. of the yearly GDP growth rates in 2018—2020. In all major macroeconomic scenarios the structural component of GDP growth rates is expected to continue to decelerate in 2018—2020. The results suggest that the delay of structural reforms is inadvisable in order to create the prerequisites to achieve economic growth rates equal to or more than the world average.

scholarly journals Economic Growth Patterns: Spatial Econometric Analysis for Russian Regions

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 289
Author(s):  
Vladimir Balash ◽  
Olga Balash ◽  
Alexey Faizliev ◽  
Elena Chistopolskaya
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Spatial Autocorrelation ◽  
Growth Rates ◽  
Growth Patterns ◽  
Weight Matrix ◽  
Russian Regions ◽  
Spatial Econometric ◽  
Per Capita ◽  
Economic Growth Rates

In this article, we analyze the σ - and β -convergence, using the data of the socio-economic development of Russian areas, and discover the role of spatial autocorrelation in regional economic development. We are considering 80 areas of the Russian Federation for the period of 2010–2017. Moran coefficients were used to estimate spatial autocorrelation. We compare the Moran scatterplots for GDP per capita and GDP growth rates per capita in 2017 and in 2014. We study the impact on raising investment in leading capital and the costs of technological innovation. We evaluate a wide range of specifications of spatial econometric models for all kinds of weight matrices. We combine standard geographical proximity with specialization proximity to assess whether they are substitutes or additions to converging economic growth rates. The weight matrix of the neighborhood and specialization similarities are used. The weight matrix of specialization similarities of the regional economies is based on data on the structure of tax payments in 82 industries. The specialization structure of the region’s economy is related to its location. Clusters obtained by matrices of specialization proximity are well separable from each other in space. The connectivity within clusters and the boundaries between them become more apparent over time. It is shown that according to the results of estimation of conditional β -convergence models, the models of 2010–2014 and 2014–2017 differ significantly. There is a statistically significant β -convergence for the period 2010–2014. There is also the presence of spatial autocorrelation. Based on the results of valuation models constructed from data after 2014, it can be concluded that the coefficient estimates for the explanatory variables are not significantly different from zero, and accordingly there is no tendency towards regional convergence in terms of economic development. The results obtained in the work are stable for the proposed models and spatial weight matrices. Territorial proximity is a more important factor than the similarity of specialization for explanation the economic growth rates of Russian regions.

scholarly journals Uncertainty in forecasts of long-run economic growth

2018 ◽  
Vol 115 (21) ◽  
pp. 5409-5414 ◽  
Author(s):  
P. Christensen ◽  
K. Gillingham ◽  
W. Nordhaus
Keyword(s):  
Economic Growth ◽  
Growth Rates ◽  
Social Insurance ◽  
Low Frequency ◽  
The United States ◽  
Long Run ◽  
Per Capita ◽  
Econometric Approach ◽  
Economic Growth Rates ◽  
Global Growth

Forecasts of long-run economic growth are critical inputs into policy decisions being made today on the economy and the environment. Despite its importance, there is a sparse literature on long-run forecasts of economic growth and the uncertainty in such forecasts. This study presents comprehensive probabilistic long-run projections of global and regional per-capita economic growth rates, comparing estimates from an expert survey and a low-frequency econometric approach. Our primary results suggest a median 2010–2100 global growth rate in per-capita gross domestic product of 2.1% per year, with a standard deviation (SD) of 1.1 percentage points, indicating substantially higher uncertainty than is implied in existing forecasts. The larger range of growth rates implies a greater likelihood of extreme climate change outcomes than is currently assumed and has important implications for social insurance programs in the United States.

scholarly journals Optimistically biased economic growth forecasts and negatively skewed annual variation

2020 ◽  
Author(s):  
Matthew G. Burgess ◽  
Ryan E. Langendorf ◽  
Tara Ippolito ◽  
Roger Pielke
Keyword(s):  
Economic Growth ◽  
Growth Rates ◽  
Time Windows ◽  
Gdp Growth ◽  
Average Growth ◽  
Per Capita Gdp ◽  
Negative Skewness ◽  
Per Capita ◽  
Growth Volatility ◽  
Growth Forecasts

Authoritative economic growth forecasts are often optimistically biased. Negatively skewed variation--negative shocks being larger than positive shocks--could contribute to bias by making long-run average growth smaller than typical-year (median) growth. This positively biases forecasts based on typical years. We compare medians and means in real per-capita GDP growth across countries, regions, and time windows from 1820-2016. Over decadal periods, we find mean growth rates <1%/y smaller than median growth rates in most countries and regions (median 0.23%/y across countries). Surprisingly, we find both large- and medium-magnitude shocks contribute to these differences, rather than only large ‘black swan’ events. We find negative skewness correlated with high levels and slow growth of per-capita GDP and population, and high per-capita GDP growth volatility, building on previous studies. We find negative skewness alone insufficient to explain recent growth over-projections by the International Monetary Fund (IMF) and the U.S. Congressional Budget Office (CBO).

scholarly journals The economic analysis of instrument variables estimation in dynamic optimal models with an application to the water consumption

2020 ◽  
Vol 66 (No. 9) ◽  
pp. 413-423
Author(s):  
Yiming He ◽  
Thomas Fullerton
Keyword(s):  
Economic Growth ◽  
Water Consumption ◽  
Dynamic Equilibrium ◽  
Growth Function ◽  
Economic Research ◽  
Consumption Function ◽  
Economic Output ◽  
Optimal Dynamic ◽  
Per Capita ◽  
Capita Output

This study examines one of the most important issues in water economic research, namely, the nexus between water consumption and economic growth. Water consumption is determined by the intersection of endogenous growth function and water consumption function, neither function can be consistently identified by comparing average quantities of water consumed at different values of observed real per capita output. The contribution of this study is an investigation of the endogenous nexus between economic output and water consumption. Water consumption function is derived using an optimal dynamic equilibrium model. Two instrument variable models are proposed with real per capita economic output specified as a function of institutional reform and urbanization, which are used to examine the nexus among water consumption, reform, urbanization, and economic growth in Guangzhou, China.

Economic Performance, Poverty, and Inequality in Rich Countries

2017 ◽  
Author(s):  
David Brady ◽  
Markus Jäntti
Keyword(s):  
Economic Growth ◽  
Business Cycle ◽  
Economic Performance ◽  
Macroeconomic Fluctuations ◽  
Macroeconomic Performance ◽  
Unemployment Rates ◽  
Poverty And Inequality ◽  
Per Capita ◽  
The Business Cycle ◽  
Rich Countries

This article explores the interrelationships among poverty, economic performance, and inequality in rich countries. It argues that poverty rises and falls with the business cycle and economic performance. Business cycle refers to macroeconomic fluctuations in economic growth, unemployment, and employment. Higher economic growth and lower unemployment rates mean more individuals employed. Because a job is one of the most effective ways to remove a household from poverty, macroeconomic performance should directly influence individual poverty. This article first describes the statistical models used to estimate the effects of economic performance on poverty before reviewing studies that assess the effects of economic performance on poverty and income inequality. In terms of economic performance, it analyzes the effects of the business cycle, economic growth, unemployment rates, and GDP per capita.

Sign in / Sign up

Export Citation Format

Share Document