Pub Date : 2009-04-01DOI: 10.1016/J.JIMONFIN.2008.12.005
P. Albuquerque, Solange Gouvea
{"title":"Canaries and Vultures: A Quantitative History of Monetary Mismanagement in Brazil","authors":"P. Albuquerque, Solange Gouvea","doi":"10.1016/J.JIMONFIN.2008.12.005","DOIUrl":"https://doi.org/10.1016/J.JIMONFIN.2008.12.005","url":null,"abstract":"","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"118160772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-03-30DOI: 10.4324/9780203088333-18
J. Cockburn
Concern is growing regarding the poverty impacts of trade liberalization. The strong general equilibrium effects of trade liberalization can only be properly analysed in a CGE model. However, the aggregate nature of CGE models is not suited to detailed poverty analysis. We bridge this gap by constructing a CGE model that explicitly models all households from a nationally representative household survey. We find complex income and consumption effects that would be missed in standard CGE models. Urban poverty falls and rural poverty increases as initial tariffs were highest for agriculture. Impacts increase with income level, resulting in rising income inequality.
{"title":"Trade Liberalisation and Poverty in Nepal: A Computable General Equilibrium Micro Simulation Analysis","authors":"J. Cockburn","doi":"10.4324/9780203088333-18","DOIUrl":"https://doi.org/10.4324/9780203088333-18","url":null,"abstract":"Concern is growing regarding the poverty impacts of trade liberalization. The strong general equilibrium effects of trade liberalization can only be properly analysed in a CGE model. However, the aggregate nature of CGE models is not suited to detailed poverty analysis. We bridge this gap by constructing a CGE model that explicitly models all households from a nationally representative household survey. We find complex income and consumption effects that would be missed in standard CGE models. Urban poverty falls and rural poverty increases as initial tariffs were highest for agriculture. Impacts increase with income level, resulting in rising income inequality.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130474269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper attempts to shed light on the efficiency/effectiveness issues of informal financial markets and the pattern of portfolio allocation shift in response to change in interest rate, in the process of financial liberalization. The two issues have been both controversial and hotly debated between proponents of the McKinnon-Shaw liberalization and Neo-structuralist economists. To examine whether interest rate changes are associated with the former or the latter view in the Congo we resort to a survey of household portfolio behavior in informal finance. Survey results suggest that informal finance is relatively effective in intermediating funds and providing financial services and access. In addition, the portfolio pattern indicates that households shift resource more from informal loan to deposits than from cash. These results provide some support for the Neostructuralists’argument; rejecting thus the McKinnon-Shaw argument that higher bank interest rates would generally increase investment.
{"title":"A Test of the Controversial Assumptions in the McKinnon-Shaw Hypothesis versus Neo-Structuralist Propositions : An Empirical Test From a Field Survey in the Congo","authors":"J. Maswana","doi":"10.18999/FORIDS.25.137","DOIUrl":"https://doi.org/10.18999/FORIDS.25.137","url":null,"abstract":"This paper attempts to shed light on the efficiency/effectiveness issues of informal financial markets and the pattern of portfolio allocation shift in response to change in interest rate, in the process of financial liberalization. The two issues have been both controversial and hotly debated between proponents of the McKinnon-Shaw liberalization and Neo-structuralist economists. To examine whether interest rate changes are associated with the former or the latter view in the Congo we resort to a survey of household portfolio behavior in informal finance. Survey results suggest that informal finance is relatively effective in intermediating funds and providing financial services and access. In addition, the portfolio pattern indicates that households shift resource more from informal loan to deposits than from cash. These results provide some support for the Neostructuralists’argument; rejecting thus the McKinnon-Shaw argument that higher bank interest rates would generally increase investment.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127804468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-10-06DOI: 10.1515/9780691186405-004
C. A. Rogers, Kenneth A. Swinnerton
We analyze slave redemption programs—the buying of slaves to give them their freedom--in a simple matching model, i.e., under the assumption that it takes time to find slaves to buy or sell. Unlike in a supply and demand framework, where sufficiently large and effective redemption programs must lead to an increase in the price at which slaves are exchanged, we find that such programs do not necessarily raise the price of slaves. We also use the model to explain why a slave redemption program can slow the flow of people into the actual state of slavery, but at the same time can increase the number of people captured to be slaves. We present contemporary examples to suggest that the weight that should be assigned to costs inflicted on the extra captured people, versus the benefits enjoyed by those redeemed, depends critically on the nature of the experience at, and just after, capture.
{"title":"Slave Redemption When it Takes Time to Redeem Slaves","authors":"C. A. Rogers, Kenneth A. Swinnerton","doi":"10.1515/9780691186405-004","DOIUrl":"https://doi.org/10.1515/9780691186405-004","url":null,"abstract":"We analyze slave redemption programs—the buying of slaves to give them their freedom--in a simple matching model, i.e., under the assumption that it takes time to find slaves to buy or sell. Unlike in a supply and demand framework, where sufficiently large and effective redemption programs must lead to an increase in the price at which slaves are exchanged, we find that such programs do not necessarily raise the price of slaves. We also use the model to explain why a slave redemption program can slow the flow of people into the actual state of slavery, but at the same time can increase the number of people captured to be slaves. We present contemporary examples to suggest that the weight that should be assigned to costs inflicted on the extra captured people, versus the benefits enjoyed by those redeemed, depends critically on the nature of the experience at, and just after, capture.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114290764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-07-06DOI: 10.1111/J.1813-6982.2004.TB00138.X
J. Aron, J. Muellbauer
South Africa adopted inflation targeting in 2000, targeting the consumer price index (CPI) excluding mortgage interest cost (or CPIX), for “metropolitan and urban areas”. Yet there is no clear technical account of the methodology of construction of CPI and CPIX by Statistics South Africa, as published by reputable government statistical agencies in other countries. This paper has two goals. First, we aim to enhance transparency by explaining the CPI methodology (as we understand it), and to encourage publication of an official technical handbook. We also raise various technical issues concerning CPI construction. Second, we produce estimates of CPIX “metropolitan areas”) back to 1970, on a consistent methodology, using monthly price indices, the appropriate weights, and linking correctly when rebasing. While the CPIX (“metropolitan and urban areas”) measure only became relevant to monetary policy setting and wage contracts from 2000, and is published monthly only from 1997, a far longer time series is required for the forecasting and modelling exercises of the South African Reserve Bank (SARB), National Treasury and others. Our measure differs in some years from that published by Statistics South Africa (published monthly only back to 1994).
{"title":"Construction of CPIX Data for Forecasting and Modelling in South Africa","authors":"J. Aron, J. Muellbauer","doi":"10.1111/J.1813-6982.2004.TB00138.X","DOIUrl":"https://doi.org/10.1111/J.1813-6982.2004.TB00138.X","url":null,"abstract":"South Africa adopted inflation targeting in 2000, targeting the consumer price index (CPI) excluding mortgage interest cost (or CPIX), for “metropolitan and urban areas”. Yet there is no clear technical account of the methodology of construction of CPI and CPIX by Statistics South Africa, as published by reputable government statistical agencies in other countries. This paper has two goals. First, we aim to enhance transparency by explaining the CPI methodology (as we understand it), and to encourage publication of an official technical handbook. We also raise various technical issues concerning CPI construction. Second, we produce estimates of CPIX “metropolitan areas”) back to 1970, on a consistent methodology, using monthly price indices, the appropriate weights, and linking correctly when rebasing. While the CPIX (“metropolitan and urban areas”) measure only became relevant to monetary policy setting and wage contracts from 2000, and is published monthly only from 1997, a far longer time series is required for the forecasting and modelling exercises of the South African Reserve Bank (SARB), National Treasury and others. Our measure differs in some years from that published by Statistics South Africa (published monthly only back to 1994).","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131158611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper highlights the key characteristics of the quantitative and qualitative approaches to poverty measurement and analysis, examines the strengths and weaknesses of each approach, and analyzes the potential for combining the two approaches in analytical work on poverty. The main conclusion of this paper is that sole reliance on either only the quantitative approach or only the qualitative approach in measuring and analyzing poverty is often likely to be less desirable than combining the two approaches. This is because there are limits to a purely quantitative approach as well as a purely qualitative approach to poverty measurement and analysis. Each approach has an appropriate time and place, but in most cases both approaches will generally be required to address different aspects of a problem and to answer questions which the other approach cannot answer as well or cannot answer at all. The need to combine the two approaches in analytical work on poverty cannot be overemphasized. There are three key ways to combine the quantitative and qualitative approaches: (i) integrating methodologies; (ii) confirming, refuting, enriching, and explaining the findings of one approach with those of the other; and (iii) merging the findings of the two approaches into one set of policy recommendations. Some ways in which the integration of methodologies can be achieved are: using quantitative survey data to determine the individuals/communities to be studied through the qualitative approach; using the quantitative survey to design the interview guide of the qualitative survey; using qualitative work to determine stratification of the quantitative sample; using qualitative work to determine the design of the quantitative survey questionnaire; using qualitative work to pretest the quantitative survey questionnaire; and/or using qualitative analyses to refine the poverty index. 'Confirming' or 'refuting' are achieved by verifying quantitative results through the qualitative approach. 'Enriching' is achieved by using qualitative work to identify issues or obtain information on variables not obtained by quantitative surveys. 'Examining' refers to generating hypothesis from qualitative work for testing through the quantitative approach. 'Explaining' involves using qualitative work to understand unanticipated results from quantitative data. In principle, each of these mechanisms may operate in either direction -- from qualitative to quantitative approaches or vice versa. 'Merging' involves analyzing the information provided both by the quantitative approach as well as the qualitative approach to derive one set of policy recommendations. The quantitative and qualitative approaches are being increasingly combined in analytical work on poverty, but there remains scope for further strengthening the links between them.
{"title":"Combining the Quantitative and Qualitative Approaches to Poverty Measurement and Analysis","authors":"H. White","doi":"10.1596/0-8213-3955-9","DOIUrl":"https://doi.org/10.1596/0-8213-3955-9","url":null,"abstract":"This paper highlights the key characteristics of the quantitative and qualitative approaches to poverty measurement and analysis, examines the strengths and weaknesses of each approach, and analyzes the potential for combining the two approaches in analytical work on poverty. The main conclusion of this paper is that sole reliance on either only the quantitative approach or only the qualitative approach in measuring and analyzing poverty is often likely to be less desirable than combining the two approaches. This is because there are limits to a purely quantitative approach as well as a purely qualitative approach to poverty measurement and analysis. Each approach has an appropriate time and place, but in most cases both approaches will generally be required to address different aspects of a problem and to answer questions which the other approach cannot answer as well or cannot answer at all. The need to combine the two approaches in analytical work on poverty cannot be overemphasized. There are three key ways to combine the quantitative and qualitative approaches: (i) integrating methodologies; (ii) confirming, refuting, enriching, and explaining the findings of one approach with those of the other; and (iii) merging the findings of the two approaches into one set of policy recommendations. Some ways in which the integration of methodologies can be achieved are: using quantitative survey data to determine the individuals/communities to be studied through the qualitative approach; using the quantitative survey to design the interview guide of the qualitative survey; using qualitative work to determine stratification of the quantitative sample; using qualitative work to determine the design of the quantitative survey questionnaire; using qualitative work to pretest the quantitative survey questionnaire; and/or using qualitative analyses to refine the poverty index. 'Confirming' or 'refuting' are achieved by verifying quantitative results through the qualitative approach. 'Enriching' is achieved by using qualitative work to identify issues or obtain information on variables not obtained by quantitative surveys. 'Examining' refers to generating hypothesis from qualitative work for testing through the quantitative approach. 'Explaining' involves using qualitative work to understand unanticipated results from quantitative data. In principle, each of these mechanisms may operate in either direction -- from qualitative to quantitative approaches or vice versa. 'Merging' involves analyzing the information provided both by the quantitative approach as well as the qualitative approach to derive one set of policy recommendations. The quantitative and qualitative approaches are being increasingly combined in analytical work on poverty, but there remains scope for further strengthening the links between them.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133787511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a growth theory that accounts for the evolution of trade policy, underlying internal class conflicts, and global income divergence over the last few centuries. By analyzing political responses to the distributional effects of international trade, this paper finds a prominent interaction between trade policy and the pattern of economic development, and suggests that the nature of the interaction depends on a country's resource abundance and distribution. As shown by the example of Western Europe, land-scarce countries will reach a developed stage through a non-monotonic evolution of trade policy. In contrast, land- abundant countries, especially those with concentrated landownership, tend to fail to take off because of landlords' opposition to industrialization.
{"title":"Endogenous Globalization and Income Divergence","authors":"Y. Sugimoto","doi":"10.2139/SSRN.680241","DOIUrl":"https://doi.org/10.2139/SSRN.680241","url":null,"abstract":"This paper develops a growth theory that accounts for the evolution of trade policy, underlying internal class conflicts, and global income divergence over the last few centuries. By analyzing political responses to the distributional effects of international trade, this paper finds a prominent interaction between trade policy and the pattern of economic development, and suggests that the nature of the interaction depends on a country's resource abundance and distribution. As shown by the example of Western Europe, land-scarce countries will reach a developed stage through a non-monotonic evolution of trade policy. In contrast, land- abundant countries, especially those with concentrated landownership, tend to fail to take off because of landlords' opposition to industrialization.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121399539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
On average, infant mortality rates are lower in more industrialized nations, yet health and mortality worsened during early industrialization in some nations. This study examines the effects of growing manufacturing employment on infant mortality across 274 Indonesian districts from 1985 to 1995, a time of rapid industrialization. Compared with cross-national studies we have a larger sample size of regions, more consistent data definitions, and better checks for causality and specification. We can also explore the causal mechanisms underlying our correlations. Overall the results suggest manufacturing employment raised living standards, housing quality, and reduced cooking with wood and coal, which helped reduce infant mortality. At the same time, pollution from factories appears quite harmful to infants. The overall effect was slightly higher infant mortality in regions that experienced greater industrialization.
{"title":"Industrialization and Infant Mortality","authors":"Maya N. Federman, D. Levine","doi":"10.2139/SSRN.704164","DOIUrl":"https://doi.org/10.2139/SSRN.704164","url":null,"abstract":"On average, infant mortality rates are lower in more industrialized nations, yet health and mortality worsened during early industrialization in some nations. This study examines the effects of growing manufacturing employment on infant mortality across 274 Indonesian districts from 1985 to 1995, a time of rapid industrialization. Compared with cross-national studies we have a larger sample size of regions, more consistent data definitions, and better checks for causality and specification. We can also explore the causal mechanisms underlying our correlations. Overall the results suggest manufacturing employment raised living standards, housing quality, and reduced cooking with wood and coal, which helped reduce infant mortality. At the same time, pollution from factories appears quite harmful to infants. The overall effect was slightly higher infant mortality in regions that experienced greater industrialization.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128190812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is well known from nonlinear aggregation theory that distributions play a central role in the determination of aggregate relations. This paper establishes a bridge between the aggregation and the inequality and growth literature by applying a log-linear aggregation method to a simple heterogeneous AK growth model. The aggregation effect is explicitly captured in the growth equation by the changes of the mean logarithmic deviation (MLD or Theil’s second measure) of the income, implying that increases in income inequality may be unambiguously associated with temporary increases in a country’s growth rate, in agreement with the empirical findings of Forbes (AER, 2000). Consequently, empirical studies of the long-run effects of income inequality may suffer from aggregation bias if the temporary effects of the MLD changes are not considered. The accelerated growth episodes observed in Brazil and China demonstrate that the increase in income inequality may have resulted in substantial temporary increases in the aggregate growth rates experienced by those countries.
从非线性聚集理论可知，分布在聚集关系的确定中起着中心作用。本文通过将对数线性聚集方法应用于一个简单的异质AK增长模型，在聚集与不等式和增长文献之间建立了一座桥梁。收入的平均对数偏差(MLD或Theil 's second measure)的变化明确地反映在增长方程中，这意味着收入不平等的增加可能与一个国家增长率的暂时增长毫无疑问地相关，这与福布斯(AER, 2000)的实证研究结果一致。因此，如果不考虑最发达国家变化的临时影响，对收入不平等长期影响的实证研究可能会出现汇总偏差。在巴西和中国观察到的加速增长表明，收入不平等的加剧可能导致这些国家的总增长率暂时大幅提高。
{"title":"Inequality-Driven Growth: Unveiling Aggregation Effects in Growth Equations","authors":"P. Albuquerque","doi":"10.2139/SSRN.527683","DOIUrl":"https://doi.org/10.2139/SSRN.527683","url":null,"abstract":"It is well known from nonlinear aggregation theory that distributions play a central role in the determination of aggregate relations. This paper establishes a bridge between the aggregation and the inequality and growth literature by applying a log-linear aggregation method to a simple heterogeneous AK growth model. The aggregation effect is explicitly captured in the growth equation by the changes of the mean logarithmic deviation (MLD or Theil’s second measure) of the income, implying that increases in income inequality may be unambiguously associated with temporary increases in a country’s growth rate, in agreement with the empirical findings of Forbes (AER, 2000). Consequently, empirical studies of the long-run effects of income inequality may suffer from aggregation bias if the temporary effects of the MLD changes are not considered. The accelerated growth episodes observed in Brazil and China demonstrate that the increase in income inequality may have resulted in substantial temporary increases in the aggregate growth rates experienced by those countries.","PeriodicalId":341672,"journal":{"name":"Development and Comp Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115283674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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