214 research outputs found

    Health and Wealth Accumulation: Evidence from Nineteenth-Century America

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    This study explores how the health of Union Army recruits while in the service affected their wealth accumulation through 1870. Wartime wounds and exposure to combat, measured by the company mortality from wounds, had strong negative effects on subsequent savings. Variables on illnesses while in service, if corrected for the potential bias arising from omitted variables by using instrumental variables, also greatly diminished wealth accumulations. The economic impact of poor health was particularly strong for unskilled workers. These results suggest that health was a powerful determinant of economic mobility in the nineteenth century. The strong influences on wealth accumulations of various infectious diseases, such as malaria, typhoid, and diarrhea, found in this study point out that the economic gains from the improvement of the disease environment should be enormous. This study also suggests that the direct economic costs of the Civil War were probably much greater than previously thought, if the persistent adverse effects of wartime experiences on veterans' health are considered.

    Rising Family Income Inequality in the United States, 1968-2000: Impacts of Changing Labor Supply, Wages, and Family Structure

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    This study estimates what fraction of the rise in family income inequality in the United States between 1968 and 2000 is accounted for by change in each of the family income components such as wages, employment, and hours worked of family heads and spouses, family structure, and other incomes. The increased disparities in other incomes and labor supply account for, respectively, 29 percent and 28 percent of the rise in the difference in income between the top 10th and bottom 10th families. Structural changes in wages, largely regarded as the major culprit of the increase in income inequality, explain less than a quarter of the rise in the measure of family income inequality. Changing fraction of families with both husband and wife and changes in the composition of the income sources account for 11 percent and 16 percent, respectively, of the widening of the income gap. The relative importance of the effect of changing labor supply declined over time, while that of wage changes increased. For the upper half of the income distribution, wage changes were the dominant cause of the increase in the gap between the richest 10th and middle-income families. For the lower half of the income distribution, in sharp contrast, changes in labor supply and other incomes were the principal causes of the growing distance between the poor and middle-income families.

    Constructing County-Level Data for Agricultural Inputs and Analyzing Agricultural Productivity, 1951-1980

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    Since the liberation from the Japanese occupation in 1945, South Korea has achieved substantial improvement in the nutritional status of the population, as indicated by the increase in adult heights. Recent studies suggest that increase in local food availability was an important contributing factor of the increased heights of the individuals born prior to 1960. Besides its significance as a long-term factor of improvement in nutritional status, measuring agricultural productivity and determining its major factors in the 1960s and 1970s is an important issue in its own right given the relative size of the Korean agricultural sector at the time. However, in-depth studies on agricultural productions in the past are restricted by the shortage of micro-level data covering the periods prior the 1980s. In this study, I collected data sources (statistical yearbooks published by each province and county) and constructed databased containing variables regarding major inputs of agricultural productions in the 1960s and 1970s. I examined how major agricultural inputs (including land, labor, agricultural machines, and chemical fertilizers) changed over time and across provinces. By linking the data on inputs with the county-level agricultural production data, I also estimated agricultural production functions, focusing on the production of rice, the most important crop in Korean agriculture. The present study is distinct from previous studies on Korean agricultural production in several respects. First, this research investigates agricultural production in Korean prior to 1980 based on county-level data, whereas most of previous studies that looked into the period are largely based on aggregate data of the country as a whole. Secondly, this study is the first to utilize the comprehensive county-level agricultural data on both outputs and inputs that are drawn from statistical yearbooks covering the two decades from 1960 to 1980. Finally, the present studies consider a wider range of agricultural inputs than those included in previous studies, including individual machinery and chemical fertilizer. The area planted with all food crops and the size of rice-cultivating area increased and reached the peak in the mid 1965s. Afterwards, it declined over time. During the Korean War (1950 to 1953), the cultivated area temporarily diminished perhaps due to wartime destructions. The area of arable lands considerably differed by province. During the three decades under study, the province with the largest planted area was Gyeongbuk, followed by Jeonnam and Gyeongnam. By the 1970s, Jeonnam overtook Gyeongnam at the number one province in terms of the arable land area. The farm population sharply fell from 1949 to 1951 as a consequence of wartime deaths. After the Korean War, the farm population gradually increased until 1967, and then declined over time thereafter. During the three decades under study, the top three provinces in terms of the size of farm population were Jeonnam, Gyeongbuk, and Gyeongnam. Even if the farm population is standardized according to age and gender compositions, these patterns of changes in labor input across times and provinces remain unchanged. The number of major agricultural machines, such as power tillers, auto sprays, and tractors, increased sharply from the early 1970s. However, the trends should be cautiously interpreted because the relatively small number of machines in the early 1960s could result from the larger number of missing observations. Nevertheless, it seems evident that the availability of agricultural machines increased over time, although we cannot be sure how much under-reporting affects the real trend. If we compare years 1969 and 1980 when the number of counties with the number of machines reported remained unchanged, the number of power tillers increased more than 30 times. The increasing trend is similar to those of auto sprays and tractors. The patterns of changes in the use of agricultural machines substantially differed by region. As in the case of agricultural machines, the use of chemical fertilizers dramatically increased from the early 1970s. Again, however, the trends should be taken cautiously because there were more counties in the 1960s where fertilizer consumption is unreported than in the 1970s. To address such potential problems, I also examined the yearly consumption divided by the number of counties (i.e., the average consumption per county). The results indicate that the rapid increasing trend largely captures the increase in the number of counties reporting fertilizer consumption. Furthermore, large fluctuations in each province’s fertilizer consumption are observed. These results suggest that samples with information on fertilizers should be selected so that variables for chemical fertilizers can be considered in the estimation of agricultural production functions. Combining the county-level data on agricultural outputs and inputs, I estimated production functions of rice, the most important crop in Korean agriculture. The variable pertaining to land input is defined as the size the rice-cultivating area (measured in hectare) in each county in a given year. For labor input, I use the standardized population living in farm households cultivating rice. Since variables pertaining to capital inputs are not universally reported in provincial or county Annual Statistics, there is a tradeoff between considering more variables on inputs and additional loss of observations. I attempt to circumvent this problem in the following two ways. Firstly, I estimate agricultural production functions excluding the variable on capital inputs, and then extend the model by including additional capital inputs to examine the effects of the sample selections arising from missing observations of capital inputs. Secondly, I only focus only on major components of capital inputs to achieve a balance between omitted variables and missed observations. Finally, I included only the counties with information on a particular type of capital input (machine or fertilizer) to avoid bias arising from underreporting in early periods. The results of regressions suggest that land and labor inputs have very strong positive relationship with the amount of rice production. In particular, the size of land input alone explains more than 95% of variations in rice productions across counties and years. If included separately, difference in labor input account for 83% of variations in rice outputs across counties and years. If the two inputs are included at the same time, the coefficient for land (0.99) is estimated much larger in magnitude than that for labor (0.05), confirming the huge importance of land in rice production in the 1960s and 1970s. If the year fixed is controlled, the coefficient for land diminishes by about 0.1 whereas the coefficient for labor increases by roughly the same magnitude. It is likely that year fixed effect captures the contributions of omitted factors that changed over time, including increased capital inputs and technical progress. The regression results imply that such omitted factors are positively related to land input, and negatively related to labor input. This is consistent with the fact that labor input decreased more rapidly than land input during the period under study. I also conducted regressions in which a measure capital input (composite index of agricultural machines) is included. The coefficient for machine is positive and statistically significant, but the additional input explains only 3% of the variations in rice production across counties and years. If machine is additionally included, the coefficients for land and labor do not change much. Inclusion of year fixed effect reduces the coefficients for land and machine, whereas the contribution of labor becomes larger in magnitude. In particular, the coefficient for machine diminishes by more than two thirds. This indicates that the estimated contributions of agricultural machines largely capture the changes in capital input and output across times. In sum, the results of regression analyses suggest that local rice production in Korea during the period from 1960 to 1979 was largely determined by land and labor inputs. Changes in these two factors explain more than 95% of variations in rice production across counties and years. It is difficult to estimate accurately the contributions of capital inputs to agricultural production because data are available only for selected capital inputs and for selected places and years. The results based on using three major agricultural machines of the time (power tillers, automatic sprays, and tractors) suggest that capital inputs also played significant roles in changing agricultural production, especially across times. Given the currently available county-level data on agricultural inputs, it would be reasonable to use the number of major agricultural machines as an index of capital input in estimating agricultural production function. Land, labor, and agricultural machines explain over 98% of the variations in rice production across counties and years. Using the data and estimated regression coefficient for each input, it will be possible to estimate the agricultural total factor productivity as well as each factor productivity in each county and year. I remain it as future research agenda to investigate how natural, institutional and technological factors (such as natural disasters, local organizations, and new methods) affected these measures of local agricultural productivity

    Who Gets Health Care?

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    Around the world, as in the United States, concern is growing about who gets health care. Individuals from different socioeconomic backgrounds face distressingly different prospects of living a healthy life. Disparities in various measures of health between the privileged and the deprived still remain wide, despite the long-term tendency toward a healthier society. Some investigators believe the shift in the health care system in industrial countries from the principle of universal access to a more market-oriented system may be one cause of the growing disparities; rising income inequality is another potential culprit. Policy makers worldwide speak of more efficiently delivering essential' health care---but disagree on what counts as essential and on the optimal mix of private and government components of service. After reviewing the economic and epidemiological literature on disparities in health and health care systems, the question of how to define essential' health care is considered. The paper concludes with a discussion of the policy implications of the analysis.

    Changes in Anthropometric Measures of Wellbeing in Korea from 1945 to 1977: Evidence from Korean Military Records

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    Although it is widely acknowledged that the rapid economic growth in South Korea during the second half of the twentieth century improved the standards of living of the population, it is not fully understood how the living conditions in South Korea changed over time, and what are the major factors that produced the changes. Research on these issues is often seriously limited by shortage of appropriate data, especially for the period between 1945 and 1960. The present study attempts to overcome the limitations of currently available data on standards of living by analyzing a newly collected sample of Korean military records. Using these sources, we have investigated how biological indices of standards of living, such as height, weight, and body-mass-index (BMI) changed across birth cohorts born between 1946 and 1957. We also examined how changes in anthropometric measures differed by province of residence, father’s occupation, and own education. The mean height of 20-year-old males in South Korea slightly declined from the 1946 birth cohort to those born in 1951, before it rapidly increased across cohorts. As for the average weight, a sharp decline and recovery of weights around the first two years of the Korean War (1950 and 1951) is observed. These results suggest that the Korean War likely affected significantly the anthropometric measures of the birth cohorts who experienced the war in utero or in early childhood. There were considerably large variations across provinces in the patterns of changes in anthropometric measures as well as the levels of the measures. Generally speaking, men who resided in Seoul and other metropolitan cities (Busan, Daegu, Gwangju, Daejeon, and Ulsan) are taller than those from non-metropolitan provinces. In contrast, men from the majority of non-metropolitan provinces are significantly shorter than those from Seoul. In sharp contrast to the results for height, urban disadvantages in weight are observed. The results of regression analyses show that the observed provincial differences in anthropometric measures do not disappear even if father’s occupation and own education are controlled. Consistent with the urban advantages found in provincial differences in height, the children of farmers turned out to be shorter that the offspring of non-farmers. Own education is positively associated with height and weight. These results suggest that the observed regional differences in the level and trend of biological standard of living in South Korea prior to the mid-1970s were probably produced by provincial differences in socioeconomic and environmental characteristics. It will be the next step of this research project to explore what are the major factors that produced the secular changes and regional differences in biological standards of living in South Korea prior to the 1970s. We are currently in the process of collecting and inputting county-level variables that are believed to be associated with net nutritional status of the population, including agricultural production, urbanization, and industrialization. We plan to conduct additional analyses by adding these factors on local environments to the variables on personal characteristics utilized in this study. We anticipate that the results of these further analyses will allow us to determine what socioeconomic changes or policy measures were the major contributors to the improvements of wellbeing of the Korean people

    Local Nutritional Availability and Adult Height: Evidence from South Korea, 1946-1977

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    It is generally accepted that the rapid economic growth in South Korea during the second half of the twentieth century greatly improved the standards of living of the country’s population. However, it is not fully understood how the living conditions in South Korea changed over time, and what are the major factors that produced the changes. For instance, there is still much to be learned about how the process of improvements differed by socioeconomic characteristics, and about how the experiences of each birth cohort differed with each other. We do not fully understand how particular economic or social changes affected the wellbeing of the population, either. Rigorous research on these issues is often seriously hampered by shortage of appropriate data, especially for the periods prior to the 1970. In our previous study (Lee 2016), supported by the 2015 Cliometric Study Program of the KDI School of Public Policy and Management, we investigated how biological indices of standards of living, such as height, weight, and body-mass-index (BMI, hereafter) changed across birth cohorts born between 1946 and 1957, based on a newly collected sample of military records for more than 18,000 conscripts. We found that the mean height at conscription slightly declined from the 1946 cohort to the1951 birth cohorts before it rapidly increased across cohorts. The mean height increased by more than two centimeters in just 6 years between 1951 and 1957. We also found considerably large variations across provinces in the patterns of changes in anthropometric measures as well as the levels of the measures. In the previous study, however, we were unable to determine what factors produced the changes in anthropometric measures across different birth cohorts and across different regions. In the present study, we investigated how nutritional availability in two crucial periods for human growth, namely, early childhood (from conception to age 2) and adolescence (from age 12 to age 16), affected the heights of Korean conscripts born from 1946 to 1957. For the purpose, we constructed province- and county-level data on agricultural productions, and matched the dataset with the sample of conscripts using the information on place of residence. We also explored how much improved nutrition during infancy and adolescence contributed to the increase in heights between the 1951 cohort and the 1957 cohort. We used the amounts of calories and three major nutrients (protein, fat, and carbohydrate) per farm household adult equivalent in a given province or county as our primary measures of local nutritional availability. In addition to nutrition variables, we considered local environmental conditions indicated by population density and nonfarm population share as well as personal and family characteristics such as season of birth, family size, and father’s occupation. We selected several different samples for whom the effects of our measure local nutritional availability on heights might differ with one another. These samples include: men from counties with information on nutritional availability, men from rural counties (baseline sample), and farmers’ sons living in rural counties. The regression results suggest that variables on local nutritional availability are generally positive and statistically significant. According to the results from the rural county sample, a person who spent infancy in a province that produced calories per farm population one standard deviation above the mean would have been about 0.2 centimeters taller at the time of conscription, if other things equal. A one standard deviation increase in protein or carbohydrate in infancy would result in an increase in height by a similar magnitude. The estimated coefficients for nutritional availability variables in adolescence are generally smaller in magnitude and statistically less significant. A major drawback of our analyses is that the true birth place of a conscript is unknown. To reduce potential measurement errors arising from geographic mobility between birth and conscription, we used a subsample of men from rural counties whose province of residence at the time of conscription is the same as the province of “original family place (Bonjeok).” If a conscript’s current address and Bonjeok are identical, it is likely that he was born in the current province of residence. About 79 percent of the full sample and 91 percent of the rural county sample reported the same current and Bonjeok province, which implies that prior geographic mobility of the conscripts in the sample was probably low. The regressions conducted based on the subsample reveal larger effects of nutritional availability on heights, compared to the baseline results. We performed height regressions with various samples alternative specifications. Adding the conscripts’ own education does not noticeably change the results. By contrast, inclusion of province fixed effect greatly increases the size of the effects of nutritional availability in early childhood. The effects of nutrition availability variables in adolescence are stronger for the 1946-1950 birth cohorts than those for the 1951-1957 birth cohorts. If the sample is limited to farmers’ sons from rural areas, the estimated coefficients for nutrition variables become larger. If the sample is extended to include men from urban counties with minimum agricultural productions, the baseline results remain little changed. We finally explored how much improved nutrition contributed to the increase in height between the 1951 and 1957 birth cohorts. The cohort trends of nutritional availability and height match well, which is consistent with the hypothesis that early-life nutrition mattered for growth of stature for the birth cohorts under investigation. For estimating the contribution of improved nutrition to the increase in height, we computed the change in height predicted by change in nutrition using height regression results and estimated change in each nutritional availability variable between 1951 and 1957. The result suggests that improved nutrition in early childhood and adolescence accounts for 30 percent to 50 percent of the increase in adult height that was gained from the 1951 and 1957 birth cohorts. Increased nutritional availability during early childhood explains a lion’s share of the contribution. The results of this study strongly suggest that nutrition was an important determining factor of biological standards of living indicated by adult height. In particular, provisions of calories and protein were strongly associated with larger stature. Food availability during early childhood was more critical for human growth than nutrition in adolescence. This result is consistent with the consensus that catch-up growth in adolescence is insufficient to fully make up for deficiencies in early childhood. Although our estimate is highly preliminary and subject to errors, it is likely that improvements in the quantity and quality of nutritional intakes that were made possible by increased incomes and enhanced agricultural productivity significantly contributed to the rise of biological standard of living indicated by changes in anthropometric measures

    Technological Changes and Employment of Older Manufacturing Workers in Early Twentieth Century America

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    This study explores how technological, organizational, and managerial changes affected the labor-market status of older male manufacturing workers in early twentieth century America. Industrial characteristics that were favorably related to the labor-market status of older industrial workers include: higher labor productivity, less capital- and material-intensive production, a shorter workday, lower intensity of work, greater job flexibility, and more formalized employment relationship. Technical innovations that improved productivity often negatively affected the quality of the work environment of older workers. These results suggest that the technological transformations in the Industrial Era brought mixed consequences to the labor-market status of older workers. On one hand, technical and organizational modifications improved the elderly workers’ employment prospect by raising labor productivity, diminishing hours of work, and formalizing employment relations. On the other hand, some types of technical innovations, which are characterized by additional requirements for physical strength, mental agility, and ability to acquire new skills, forced older workers out of their jobs. Since the pace and nature of technical change considerably differed across industries, and possibly across firms within the same industry, the labor-market experiences of individual older workers should have been highly heterogeneous.

    Labor Force Participation of Older Males in Korea: 1955-2005

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    This study estimates the labor force participation rate (LFPR) of older males in Korea from 1955 to 2005, and analyzes the effects of several determining factors on labor force participation decisions at older ages. The LFPR of older men increased substantially from the mid-1960s to the late-1990s. This pattern is in sharp contrast to the historical experiences of most OECD countries, where the LFPR of older males declined rapidly over the last century. The rise in the LFPR of older males in Korea between 1965 and 1995 is largely explained by the dramatic increase in the labor-market activity of the rural elderly population. The results of regression analyses suggest that the acceleration of population aging in rural areas due to the selective out-migration of younger persons was the major cause of the sharp increase in the LFPR of older males. It is likely that the relative decline of the rural economy in the course of industrialization made it increasingly difficult for the rural elderly population to save for retirement.
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