This document discusses spatial data analysis of productivity convergence across regions in Portugal based on convergence theories and spatial econometrics. It analyzes productivity data for different sectors in Portuguese regions using Moran's I statistics, finding positive spatial autocorrelation in productivity for agriculture, services, industry, and total sectors. The document also reviews theories of absolute and conditional convergence and studies examining spatial effects on productivity convergence. It proposes using spatial econometric models and specification tests to analyze conditional productivity convergence across Portuguese regions from 1995 to 2002 while controlling for spatial effects.
This document presents a spatial model analyzing productivity convergence across regions in Portugal from 1995 to 2002. It builds a model using cross-section estimation methods to examine the influence of spatial effects and human capital on conditional productivity convergence across economic sectors in mainland Portugal's NUTS III regions. The results indicate that productivity convergence was greatest in industry and was conditioned by human capital, particularly higher education levels. Spatial spillover effects and spatial autocorrelation did not significantly impact productivity convergence across regions and sectors in the period studied.
1) The document analyzes spatial effects on conditional product convergence across parishes in mainland Portugal from 1991 to 2001 using cross-section estimation methods.
2) Estimation results found no evidence of convergence, as the population is concentrated in coastal areas, and spatial spillover effects and spatial autocorrelation influence parish productivity changes.
3) Productivity diverged across parishes over this period, a concern given population concentration in coastal areas and depopulation of inland regions.
This document discusses testing alternative specifications of Verdoorn's Law, which relates productivity growth and output growth, using data from the Portuguese economy at regional and sectoral levels from 1995-1999. The original Verdoorn specification is estimated along with a new specification that includes additional variables like capital investment, trade flows, and labor concentration to examine how economies of scale are influenced by factors from theories of polarization and agglomeration. Regression analysis of the panel data shows the original Verdoorn specification is more robust and confirms increasing returns to scale, while the additional variables have little influence on economies of scale.
1) The document presents an alternative model for Portugal based on Keynesian theory, testing Verdoorn's Law which relates productivity and output growth for Portugal's regions and sectors from 1995-1999.
2) Additional variables are tested in Verdoorn's Law, including trade flows, capital accumulation, and labor concentration, but they have little influence on scale economies.
3) Estimations using the original Verdoorn equation confirm the presence of increasing returns to scale at regional and sectoral levels in Portugal, while the expanded model with new variables provides little improvement.
This document analyzes spatial effects and human capital on productivity convergence across Portuguese regions between 1995 and 2002 using cross-section estimation methods. It first presents theoretical considerations on spatial econometrics and models of convergence. It then analyzes the data using spatial econometrics techniques and presents estimates. Finally, it highlights the main conclusions that productivity is subject to spatial autocorrelation in some sectors, and considering spatial effects and human capital as variables, absolute convergence is greatest in industry and higher education has the strongest positive effect on productivity growth.
1) This study analyzes labor mobility and conditional economic convergence in Portugal between 1991 and 2001 at the parish and NUTS III levels.
2) Estimates of a net migration model show that availability of housing had a statistically significant positive influence on net migration to NUTS III regions, but there were no spatial spillover effects.
3) Estimates of a conditional convergence model with spatial effects found no clear evidence of convergence between Portuguese parishes over the period studied and showed spatial spillover effects conditioned convergence.
Javier Ordóñez. Real unit labour costs in Eurozone countries: Drivers and clu...Eesti Pank
This document analyzes real unit labor costs (RULC) in 11 Eurozone countries from 1980 to 2012 to examine divergence forces. RULC is decomposed into components including labor productivity and nominal compensation per employee. A cluster analysis is performed using the Phillips and Sul methodology to test for convergence or divergence among the countries. The analysis finds that countries can be grouped into clusters based on their RULC performance, indicating latent divergence forces rather than overall convergence across the Eurozone. Internal devaluation policies are deemed insufficient and technology differences are identified as the main driver of observed divergences.
1) This document discusses testing different versions of Verdoorn's Law, which posits a relationship between productivity and output growth, using regional data from Portugal from 1995-1999.
2) It examines specifications by Kaldor and Rowthorn, and also tests an expanded version that includes additional variables like capital investment, trade flows, and labor concentration.
3) Estimates using various models and data for different sectors find evidence of increasing returns to scale, particularly in industry and services, providing support for Verdoorn's Law and cumulative causation of regional economic divergence in Portugal.
This document presents a spatial model analyzing productivity convergence across regions in Portugal from 1995 to 2002. It builds a model using cross-section estimation methods to examine the influence of spatial effects and human capital on conditional productivity convergence across economic sectors in mainland Portugal's NUTS III regions. The results indicate that productivity convergence was greatest in industry and was conditioned by human capital, particularly higher education levels. Spatial spillover effects and spatial autocorrelation did not significantly impact productivity convergence across regions and sectors in the period studied.
1) The document analyzes spatial effects on conditional product convergence across parishes in mainland Portugal from 1991 to 2001 using cross-section estimation methods.
2) Estimation results found no evidence of convergence, as the population is concentrated in coastal areas, and spatial spillover effects and spatial autocorrelation influence parish productivity changes.
3) Productivity diverged across parishes over this period, a concern given population concentration in coastal areas and depopulation of inland regions.
This document discusses testing alternative specifications of Verdoorn's Law, which relates productivity growth and output growth, using data from the Portuguese economy at regional and sectoral levels from 1995-1999. The original Verdoorn specification is estimated along with a new specification that includes additional variables like capital investment, trade flows, and labor concentration to examine how economies of scale are influenced by factors from theories of polarization and agglomeration. Regression analysis of the panel data shows the original Verdoorn specification is more robust and confirms increasing returns to scale, while the additional variables have little influence on economies of scale.
1) The document presents an alternative model for Portugal based on Keynesian theory, testing Verdoorn's Law which relates productivity and output growth for Portugal's regions and sectors from 1995-1999.
2) Additional variables are tested in Verdoorn's Law, including trade flows, capital accumulation, and labor concentration, but they have little influence on scale economies.
3) Estimations using the original Verdoorn equation confirm the presence of increasing returns to scale at regional and sectoral levels in Portugal, while the expanded model with new variables provides little improvement.
This document analyzes spatial effects and human capital on productivity convergence across Portuguese regions between 1995 and 2002 using cross-section estimation methods. It first presents theoretical considerations on spatial econometrics and models of convergence. It then analyzes the data using spatial econometrics techniques and presents estimates. Finally, it highlights the main conclusions that productivity is subject to spatial autocorrelation in some sectors, and considering spatial effects and human capital as variables, absolute convergence is greatest in industry and higher education has the strongest positive effect on productivity growth.
1) This study analyzes labor mobility and conditional economic convergence in Portugal between 1991 and 2001 at the parish and NUTS III levels.
2) Estimates of a net migration model show that availability of housing had a statistically significant positive influence on net migration to NUTS III regions, but there were no spatial spillover effects.
3) Estimates of a conditional convergence model with spatial effects found no clear evidence of convergence between Portuguese parishes over the period studied and showed spatial spillover effects conditioned convergence.
Javier Ordóñez. Real unit labour costs in Eurozone countries: Drivers and clu...Eesti Pank
This document analyzes real unit labor costs (RULC) in 11 Eurozone countries from 1980 to 2012 to examine divergence forces. RULC is decomposed into components including labor productivity and nominal compensation per employee. A cluster analysis is performed using the Phillips and Sul methodology to test for convergence or divergence among the countries. The analysis finds that countries can be grouped into clusters based on their RULC performance, indicating latent divergence forces rather than overall convergence across the Eurozone. Internal devaluation policies are deemed insufficient and technology differences are identified as the main driver of observed divergences.
1) This document discusses testing different versions of Verdoorn's Law, which posits a relationship between productivity and output growth, using regional data from Portugal from 1995-1999.
2) It examines specifications by Kaldor and Rowthorn, and also tests an expanded version that includes additional variables like capital investment, trade flows, and labor concentration.
3) Estimates using various models and data for different sectors find evidence of increasing returns to scale, particularly in industry and services, providing support for Verdoorn's Law and cumulative causation of regional economic divergence in Portugal.
The document discusses the space-time (in)consistency between national accounts GDP statistics and purchasing power parity (PPP) exchange rates. It finds that while non-homotheticity and chain index errors could theoretically cause inconsistencies, empirical evidence suggests data errors are likely the primary cause of observed inconsistencies. The author argues that improving data quality and developing more sophisticated methods of combining national accounts and PPP data could help reduce inconsistencies. Comments praise the paper's ambition but raise questions about potential biases in the author's tests and suggest alternative approaches like state space models warrant further investigation.
We analyse a small open economy with a tradable and a sheltered sector. If the unions that operate in each sector coordinate their wage demands sectorwise, the choice of monetary regime – floating cum inflation target vs. EMU – may affect the relative wages and prices of the economy. We show that EMU results in lower prices for tradable goods and lower real wages in the traded sector while opposite results hold for sheltered sector prices and wages. Thus, if large unions behave strategically, the choice of monetary regime has far-reaching structural implications.
This study analyzes how the exchange rate elasticity of exports has changed over time and across countries to determine if currency wars are worth fighting. The analysis uses panel data from 7 countries from 1990-2014 and finds that the elasticity of total exports has declined over this period. Specifically, the elasticity fell from an average of 0.63 in 1990-2003 to 0.4 in 2004-2014. Additional analysis shows this decline preceded the global financial crisis, suggesting cyclical factors are not the sole driver. In conclusion, the effectiveness of currency depreciation in boosting exports appears to have decreased over time.
This document presents a model of the Portuguese economy based on Keynesian theory, specifically analyzing Verdoorn's Law which posits a relationship between productivity and output growth. It examines the specifications of Kaldor (1966) and Rowthorn (1975) by estimating these relationships for Portugal's 28 regions from 1995-1999 across different economic sectors. The results found the industry sector exhibited increasing returns to scale most strongly. Overall, Verdoorn's equation provided the most statistically significant and explanatory results, supporting the conclusion that productivity is endogenous and driven by regional and sectoral output growth.
This document presents research on net migration and productivity convergence across Portuguese regions from 1995 to 2002. Regression analysis of net migration rates for NUTS II regions from 1996-2002 found that growth rates and unemployment influenced migration positively and negatively, respectively. Analysis of NUTS III regions found conditional convergence in industry but divergence in agriculture, possibly influenced by human capital levels. Cross-section estimates also examined the influence of spatial effects and human capital on productivity convergence across economic sectors in NUTS III regions over this period.
Option pricing under multiscale stochastic volatilityFGV Brazil
The stochastic volatility model proposed by Fouque, Papanicolaou, and Sircar (2000) explores a fast and a slow time-scale fluctuation of the volatility process to end up with a parsimonious way of capturing the volatility smile implied by close to the money options. In this paper, we test three different models of these authors using options on the S&P 500. First, we use model independent statistical tools to demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility. Our analysis of market data shows that both time-scales are statistically significant. We also provide a calibration method using observed option prices as represented by the so-called term structure of implied volatility. The resulting approximation is still independent of the particular details of the volatility model and gives more flexibility in the parametrization of the implied volatility surface. In addition, to test the model’s ability to price options, we simulate options prices using four different specifications for the Data generating Process. As an illustration, we price an exotic option.
Ongoing Master Thesis by Cristina Tessari and Caio Almeida;
EPGE Brazilian School of Economics and Finance.
http://www.fgv.br/epge/en
Empirical test of the relationship between import substitution and trade perf...Alexander Decker
This document summarizes a study that empirically tested the relationship between import substitution policies and trade performance in Zimbabwe from 1980 to 2009. The study used a vector error correction model to analyze the long-run and short-run relationships between net exports (the measure of trade performance), import tariffs, and exchange rates. The results showed cointegration, indicating a long-run equilibrium relationship between the variables. Specifically, it found that real exchange rate depreciation was negatively associated with net exports and negatively related to import tariffs in the long-run. It also found that import tariffs had a negative relationship with net exports in the long-run.
A Primer on Cointegration: Application to Nigerian Gross Domestic Product and...IOSR Journals
This document examines the relationship between gross domestic product (GDP) and exports (EXP) in Nigeria from 1970 to 2007 using cointegration analysis. Autocorrelation tests show that GDP and EXP are both non-stationary. Applying the Augmented Engle-Granger method reveals that regressing GDP on EXP produces a cointegrating relationship, not a spurious one. An error correction model indicates that while GDP and EXP have a long-term equilibrium relationship, GDP does not fully adjust to changes in EXP in the short run.
This study addresses the connection between reorganization and unemployment in the labour market. Reorganization of regional labour markets measured by simultaneous gross migration flows lowers the unemployment rate, based on evidence from a panel of Finnish regions. However, reorganization is shown to be unrelated to long-term unemployment.
This document summarizes a presentation on analyzing the sensitivity of dynamic stochastic general equilibrium (DSGE) models when evaluating structural reforms. It discusses how DSGE models are commonly used to evaluate reforms like labor and goods market deregulation. However, the effects of reforms in DSGE models strongly depend on assumptions like household preferences. The presentation finds that calibrating parameters like the Frisch elasticity and habits can significantly impact welfare and output results. It emphasizes the need for sensitivity analysis when using DSGE models to assess structural reforms, as economic gains do not always align with welfare improvements.
1) MELEZE is a DSGE model developed by Insee to analyze the French economy within the Euro Area. It aims to complement Insee's existing macroeconometric model Mésange.
2) The model features households, firms in monopolistic competition, workers in monopolistic competition, sticky prices and wages, and two countries within a monetary union. It explores fiscal analysis and the effects of structural reforms.
3) The document outlines the model's key components, including the government's behavior, financial markets, and steady state restrictions. It also discusses conducting sensitivity analyses when examining the channels and quantitative effects of structural reforms.
This document contains loan-level data for over 100 commercial mortgage-backed security loans. It includes key information about each loan such as the name, current balance, interest rate, loan-to-value ratio, debt service coverage ratio, and performance status. The largest loans by balance include the Hilton Worldwide Portfolio and the Ala Moana Portfolio, a multi-property portfolio totaling over $1.4 billion across several transactions. The document provides a snapshot of the major loans that make up the commercial mortgage market.
This document summarizes research testing alternative specifications of Verdoorn's Law for Portuguese regions from 1986-1994. It analyzes the relationship between productivity, employment, and output growth. It also examines convergence in productivity across regions and the importance of natural resources and industrial policies for manufacturing concentration. Regression models are estimated using regional and industry data to explore these relationships.
This document analyzes factors that influence geographic concentration of manufacturing industries in Portugal's regions from 1980 to 1999. It estimates a Rybczynski equation matrix for different industries in each region. Estimates are shown for periods 1980-1985, 1986-1994, 1980-1994, and 1995-1999. The results show manufacturing location in Portugal is mostly explained by specific regional factors like labor, agriculture, extraction industries and construction. Effects from spillovers and industrial policy have little importance. Overall natural advantages and local resources, especially labor, remain important for explaining geographic concentration of industries in Portuguese regions.
This document analyzes agglomeration in Portuguese regions using New Economic Geography models. It tests the Verdoorn Law, which states that productivity growth is related to output growth, using data from Portuguese regions from 1995-1999. The results show the industry sector exhibits the greatest economies of scale, followed by services. Testing different specifications, the findings provide some support for the Verdoorn Law while also indicating spatial effects influence productivity across economic sectors in Portugal.
This document lists the names of 27 major supermarket chains in the United States along with their contact information and websites. Some of the largest chains included are Kroger, Safeway, Costco Wholesale, Supervalu, Publix, Ahold USA, Delhaize America, H-E-B, and Whole Foods Market. Contact phone numbers and emails are provided for representatives from the corporate communications, marketing, or public relations departments of each company.
This document analyzes spatial effects and convergence theory in the context of regional productivity in Portugal between 1995-2002. It finds:
1) Productivity shows positive spatial autocorrelation, indicating regions with similar productivity levels are clustered together, especially in agriculture and services.
2) There are stronger indications of absolute convergence in industry compared to other sectors.
3) Estimates show convergence is conditioned by spatial spillover effects, human capital levels, and spatial dependencies in errors and variables across regions.
This document presents a spatial model analyzing the influence of spatial effects on productivity convergence across economic sectors in regions of mainland Portugal from 1995 to 2002. The author builds a model of conditional convergence with spatial lag and spatial error components. Estimation results show productivity convergence was greatest in the industry sector. While some spatial autocorrelation was found, spatial spillover effects did not significantly influence productivity convergence across sectors in the studied regions and time period.
This study analyzes spatial data and productivity convergence across regions in Portugal using spatial econometric techniques. Productivity is measured for different economic sectors from 1995-2005.
Key findings:
1) Productivity is positively spatially autocorrelated in services, indicating neighboring regions influence each other.
2) Agriculture and services show positive spatial autocorrelation in productivity from 1995-2002.
3) Industry shows the strongest tendencies towards absolute productivity convergence across regions.
The study uses techniques like Moran's I statistic and LISA maps to identify spatial clusters of high and low productivity values and determine if productivity is spatially dependent between neighboring regions in Portugal.
This document analyzes spatial data from Portuguese regions across several economic sectors based on Keynesian theory and spatial econometrics. Productivity is found to exhibit positive spatial autocorrelation, especially in services. All sectors together also show positive autocorrelation in productivity. The study tests Verdoorn's Law relating productivity and output growth using spatial econometric techniques. Models include spatial lag and error components to account for spillover effects between neighboring regions.
The document discusses the space-time (in)consistency between national accounts GDP statistics and purchasing power parity (PPP) exchange rates. It finds that while non-homotheticity and chain index errors could theoretically cause inconsistencies, empirical evidence suggests data errors are likely the primary cause of observed inconsistencies. The author argues that improving data quality and developing more sophisticated methods of combining national accounts and PPP data could help reduce inconsistencies. Comments praise the paper's ambition but raise questions about potential biases in the author's tests and suggest alternative approaches like state space models warrant further investigation.
We analyse a small open economy with a tradable and a sheltered sector. If the unions that operate in each sector coordinate their wage demands sectorwise, the choice of monetary regime – floating cum inflation target vs. EMU – may affect the relative wages and prices of the economy. We show that EMU results in lower prices for tradable goods and lower real wages in the traded sector while opposite results hold for sheltered sector prices and wages. Thus, if large unions behave strategically, the choice of monetary regime has far-reaching structural implications.
This study analyzes how the exchange rate elasticity of exports has changed over time and across countries to determine if currency wars are worth fighting. The analysis uses panel data from 7 countries from 1990-2014 and finds that the elasticity of total exports has declined over this period. Specifically, the elasticity fell from an average of 0.63 in 1990-2003 to 0.4 in 2004-2014. Additional analysis shows this decline preceded the global financial crisis, suggesting cyclical factors are not the sole driver. In conclusion, the effectiveness of currency depreciation in boosting exports appears to have decreased over time.
This document presents a model of the Portuguese economy based on Keynesian theory, specifically analyzing Verdoorn's Law which posits a relationship between productivity and output growth. It examines the specifications of Kaldor (1966) and Rowthorn (1975) by estimating these relationships for Portugal's 28 regions from 1995-1999 across different economic sectors. The results found the industry sector exhibited increasing returns to scale most strongly. Overall, Verdoorn's equation provided the most statistically significant and explanatory results, supporting the conclusion that productivity is endogenous and driven by regional and sectoral output growth.
This document presents research on net migration and productivity convergence across Portuguese regions from 1995 to 2002. Regression analysis of net migration rates for NUTS II regions from 1996-2002 found that growth rates and unemployment influenced migration positively and negatively, respectively. Analysis of NUTS III regions found conditional convergence in industry but divergence in agriculture, possibly influenced by human capital levels. Cross-section estimates also examined the influence of spatial effects and human capital on productivity convergence across economic sectors in NUTS III regions over this period.
Option pricing under multiscale stochastic volatilityFGV Brazil
The stochastic volatility model proposed by Fouque, Papanicolaou, and Sircar (2000) explores a fast and a slow time-scale fluctuation of the volatility process to end up with a parsimonious way of capturing the volatility smile implied by close to the money options. In this paper, we test three different models of these authors using options on the S&P 500. First, we use model independent statistical tools to demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility. Our analysis of market data shows that both time-scales are statistically significant. We also provide a calibration method using observed option prices as represented by the so-called term structure of implied volatility. The resulting approximation is still independent of the particular details of the volatility model and gives more flexibility in the parametrization of the implied volatility surface. In addition, to test the model’s ability to price options, we simulate options prices using four different specifications for the Data generating Process. As an illustration, we price an exotic option.
Ongoing Master Thesis by Cristina Tessari and Caio Almeida;
EPGE Brazilian School of Economics and Finance.
http://www.fgv.br/epge/en
Empirical test of the relationship between import substitution and trade perf...Alexander Decker
This document summarizes a study that empirically tested the relationship between import substitution policies and trade performance in Zimbabwe from 1980 to 2009. The study used a vector error correction model to analyze the long-run and short-run relationships between net exports (the measure of trade performance), import tariffs, and exchange rates. The results showed cointegration, indicating a long-run equilibrium relationship between the variables. Specifically, it found that real exchange rate depreciation was negatively associated with net exports and negatively related to import tariffs in the long-run. It also found that import tariffs had a negative relationship with net exports in the long-run.
A Primer on Cointegration: Application to Nigerian Gross Domestic Product and...IOSR Journals
This document examines the relationship between gross domestic product (GDP) and exports (EXP) in Nigeria from 1970 to 2007 using cointegration analysis. Autocorrelation tests show that GDP and EXP are both non-stationary. Applying the Augmented Engle-Granger method reveals that regressing GDP on EXP produces a cointegrating relationship, not a spurious one. An error correction model indicates that while GDP and EXP have a long-term equilibrium relationship, GDP does not fully adjust to changes in EXP in the short run.
This study addresses the connection between reorganization and unemployment in the labour market. Reorganization of regional labour markets measured by simultaneous gross migration flows lowers the unemployment rate, based on evidence from a panel of Finnish regions. However, reorganization is shown to be unrelated to long-term unemployment.
This document summarizes a presentation on analyzing the sensitivity of dynamic stochastic general equilibrium (DSGE) models when evaluating structural reforms. It discusses how DSGE models are commonly used to evaluate reforms like labor and goods market deregulation. However, the effects of reforms in DSGE models strongly depend on assumptions like household preferences. The presentation finds that calibrating parameters like the Frisch elasticity and habits can significantly impact welfare and output results. It emphasizes the need for sensitivity analysis when using DSGE models to assess structural reforms, as economic gains do not always align with welfare improvements.
1) MELEZE is a DSGE model developed by Insee to analyze the French economy within the Euro Area. It aims to complement Insee's existing macroeconometric model Mésange.
2) The model features households, firms in monopolistic competition, workers in monopolistic competition, sticky prices and wages, and two countries within a monetary union. It explores fiscal analysis and the effects of structural reforms.
3) The document outlines the model's key components, including the government's behavior, financial markets, and steady state restrictions. It also discusses conducting sensitivity analyses when examining the channels and quantitative effects of structural reforms.
This document contains loan-level data for over 100 commercial mortgage-backed security loans. It includes key information about each loan such as the name, current balance, interest rate, loan-to-value ratio, debt service coverage ratio, and performance status. The largest loans by balance include the Hilton Worldwide Portfolio and the Ala Moana Portfolio, a multi-property portfolio totaling over $1.4 billion across several transactions. The document provides a snapshot of the major loans that make up the commercial mortgage market.
This document summarizes research testing alternative specifications of Verdoorn's Law for Portuguese regions from 1986-1994. It analyzes the relationship between productivity, employment, and output growth. It also examines convergence in productivity across regions and the importance of natural resources and industrial policies for manufacturing concentration. Regression models are estimated using regional and industry data to explore these relationships.
This document analyzes factors that influence geographic concentration of manufacturing industries in Portugal's regions from 1980 to 1999. It estimates a Rybczynski equation matrix for different industries in each region. Estimates are shown for periods 1980-1985, 1986-1994, 1980-1994, and 1995-1999. The results show manufacturing location in Portugal is mostly explained by specific regional factors like labor, agriculture, extraction industries and construction. Effects from spillovers and industrial policy have little importance. Overall natural advantages and local resources, especially labor, remain important for explaining geographic concentration of industries in Portuguese regions.
This document analyzes agglomeration in Portuguese regions using New Economic Geography models. It tests the Verdoorn Law, which states that productivity growth is related to output growth, using data from Portuguese regions from 1995-1999. The results show the industry sector exhibits the greatest economies of scale, followed by services. Testing different specifications, the findings provide some support for the Verdoorn Law while also indicating spatial effects influence productivity across economic sectors in Portugal.
This document lists the names of 27 major supermarket chains in the United States along with their contact information and websites. Some of the largest chains included are Kroger, Safeway, Costco Wholesale, Supervalu, Publix, Ahold USA, Delhaize America, H-E-B, and Whole Foods Market. Contact phone numbers and emails are provided for representatives from the corporate communications, marketing, or public relations departments of each company.
This document analyzes spatial effects and convergence theory in the context of regional productivity in Portugal between 1995-2002. It finds:
1) Productivity shows positive spatial autocorrelation, indicating regions with similar productivity levels are clustered together, especially in agriculture and services.
2) There are stronger indications of absolute convergence in industry compared to other sectors.
3) Estimates show convergence is conditioned by spatial spillover effects, human capital levels, and spatial dependencies in errors and variables across regions.
This document presents a spatial model analyzing the influence of spatial effects on productivity convergence across economic sectors in regions of mainland Portugal from 1995 to 2002. The author builds a model of conditional convergence with spatial lag and spatial error components. Estimation results show productivity convergence was greatest in the industry sector. While some spatial autocorrelation was found, spatial spillover effects did not significantly influence productivity convergence across sectors in the studied regions and time period.
This study analyzes spatial data and productivity convergence across regions in Portugal using spatial econometric techniques. Productivity is measured for different economic sectors from 1995-2005.
Key findings:
1) Productivity is positively spatially autocorrelated in services, indicating neighboring regions influence each other.
2) Agriculture and services show positive spatial autocorrelation in productivity from 1995-2002.
3) Industry shows the strongest tendencies towards absolute productivity convergence across regions.
The study uses techniques like Moran's I statistic and LISA maps to identify spatial clusters of high and low productivity values and determine if productivity is spatially dependent between neighboring regions in Portugal.
This document analyzes spatial data from Portuguese regions across several economic sectors based on Keynesian theory and spatial econometrics. Productivity is found to exhibit positive spatial autocorrelation, especially in services. All sectors together also show positive autocorrelation in productivity. The study tests Verdoorn's Law relating productivity and output growth using spatial econometric techniques. Models include spatial lag and error components to account for spillover effects between neighboring regions.
This study analyzes spatial autocorrelation and the Verdoorn Law for productivity in Portugal's NUTS III regions from 1995-1999 and 2000-2005. Productivity is found to have positive spatial autocorrelation, especially in services sectors. Spatial spillovers, lags, and errors are found to influence the Verdoorn relationship between regions. Results differ between periods as expected, with stronger effects in the second period when Portugal benefited more from EU and national support programs. The consideration of spatial effects in regional analysis is becoming increasingly important.
1) This study analyzes spatial effects and conditional convergence theory at the parish level in mainland Portugal from 1991-2001.
2) Statistical analysis shows some positive spatial autocorrelation of product growth, with high-high autocorrelation in coastal parishes and low-low autocorrelation in inland parishes.
3) Estimates using OLS and maximum likelihood methods indicate that when spatial spillover effects are considered, there are indications that spatial factors condition convergence of parish productivity over this period.
This document presents a model for analyzing net migration between Portuguese regions from 1991 to 2001. The empirical analysis finds that housing availability, measured as the growth rate in the number of houses in a region compared to other regions, is the main determinant of migration patterns between regions. Spatial autocorrelation tests find no influence of neighboring regions' net migration or other factors on a given region's migration rates. The model and results suggest housing supply was the primary driver of labor mobility between Portuguese regions during this time period.
This document discusses spatial effects and Verdoorn's Law in the Portuguese context. It summarizes previous studies that have analyzed Verdoorn's Law considering spatial spillover effects. This study aims to test Verdoorn's Law for economic sectors in Portuguese regions from 1995 to 1999 and 2000 to 2005 using cross-section spatial econometrics techniques. It presents theoretical considerations of spatial econometrics and explains the models to be considered.
This document presents research analyzing net migration between Portuguese regions from 1996-2002 at the NUTS II level and 1991 and 2001 at the NUTS III level. Theoretical models of migration determinants are discussed, and empirical analysis is conducted using statistical data from the Portuguese National Institute of Statistics. Regression analysis finds that at the NUTS II level, real output growth positively impacts migration while unemployment and agricultural employment negatively impact it. At the NUTS III level, amenities like housing availability are also important determinants of migration.
1. The document analyzes the influence of spatial effects on productivity across sectors and regions in Portugal from 1995-1999 and 2000-2005 using cross-section estimation methods.
2. It considers previous studies on spatial econometrics and Verdoorn's Law, and explains the models, data analysis techniques, and estimations used to test for spatial effects.
3. The results find evidence of spatial autocorrelation and spillover effects, with the strongest support for Verdoorn's Law in industry. This suggests policies to modernize industry could help it benefit from spatial spillovers.
1) The document presents a spatial model of the Keynesian theory for Portugal's regions based on analyzing productivity influences across economic sectors from 1995-1999 and 2000-2005.
2) Spatial effects like spillovers, lags, and errors were found to influence productivity relationships defined by Verdoorn's law for some sectors and time periods in Portuguese regions.
3) The study uses cross-section estimation methods to test Verdoorn's law for agriculture, industry, services and total sectors across 28 mainland Portuguese regions, considering spatial effects.
This document analyzes the influence of spatial effects on productivity across economic sectors in Portuguese regions from 1995 to 2005. It first reviews previous studies on spatial econometrics and Verdoorn's Law. It then explains the models and techniques used, including spatial lag and error models. Estimations of Verdoorn's Law are conducted taking spatial effects into account. The conclusions found spatial autocorrelation influences productivity differently across sectors and time periods, and that industry had the strongest relationship with scaled income growth but lowest spatial spillovers in the first period analyzed.
This document presents a model for analyzing net migration between Portuguese regions from 1996 to 2002. The model shows that regional mobility is positively influenced by output growth and negatively by unemployment rates and the agricultural sector size. Regression analysis of the data from Portuguese national statistics supports the model's conclusions. Specifically, regions with higher unemployment and more agricultural jobs attracted fewer migrants, while regions with stronger economic growth attracted more.
Konvergoituvatko eri maiden tuottavuustasot? Lähentyvätkö kehittyvät maat kehittyneitä maita? Mitkä maaryhmät konvergoituvat? Tässä tutkimuksessa pyritään antamaan vastauksia edelle esitettyihin kysymyksiin tarkastelemalla työn tuottavuuden absoluuttista konvergenssia ja sigma-konvergenssia Penn World Table 9.0 aineistolla. Absoluuttisella konvergenssilla tarkoitetaan yksinkertaistaen sitä, että mitä alempi taso jollakin taloudellisella mittarilla on suhteessa muihin maihin, sitä suurempi on sen kasvuaste. Sigma-konvergenssilla tarkoitetaan sitä, että jonkin taloudellisen mittarin eri maiden tasojen hajonta pienenee jollakin aikavälillä. Tässä tutkimuksessa testataan konvergoituvatko tiettyjen maaryhmien tuottavuustasot. Nämä maaryhmät ovat seuraavat kansainväliset organisaatiot: OECD, EU ja APEC. Lisäksi testataan konvergoituvatko seuraavien maanosien maat keskenään: Afrikka, Aasia, Eurooppa ja Etelä-Amerikka. Tulosten mukaan konvergoitumista esiintyy seuraavissa maaryhmissä: OECD, EU, APEC, Eurooppa ja Aasia. Tulosten mukaan Afrikassa ja Etelä-Amerikassa konvergoituminen on kuitenkin epävarmaa tai jopa olematonta.
The Causal Analysis of the Relationship between Inflation and Output Gap in T...inventionjournals
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SPATIAL DATA ANALYSIS BASED ON THE CONVERGENCE THEORIES FOR PORTUGAL
1. SPATIAL DATA ANALYSIS BASED ON THE CONVERGENCE THEORIES FOR
PORTUGAL
Vítor João Pereira Domingues Martinho
Escola Superior Agrária, Instituto Politécnico de Viseu, Quinta da Alagoa,
Estrada de Nelas, Ranhados, 3500 - 606 VISEU
Centro de Estudos em Educação, Tecnologias e Saúde (CI&DETS)
Portugal
e-mail: vdmartinho@esav.ipv.pt
ABSTRACT:
This study analyses the data of the Portuguese regions, for the different sectors, based on the
convergence theories and on the spatial econometrics instruments. To analyse the data, Moran’s I
statistics is considered, and it is stated that productivity is subject to positive spatial autocorrelation,
above all, in agriculture and services. Industry and the total of all sectors present indications that they
are subject to positive spatial autocorrelation in productivity.
Keywords: Spatial Econometric; Convergence theories; Portuguese Regions
2. 1. Introduction
There are few known studies concerning conditional productivity convergence with spatial
effects. Fingleton (2001), for example has found spatial correlation at the level of productivity when,
using data from 178 regions of the European Union, he introduced spillover effects in a model of
endogenous growth. Abreu et al. (2004) have investigated the spatial distribution of the rates of total
productivity growth of factors using exploratory analyses of spatial data and other techniques of
spatial econometrics. The sample consists of 73 countries and covers the period from 1960 to 2000.
They have found significant spatial correlation in the rates of total factor productivity growth,
indicating that high and low values tend to concentrate in space, forming the so-called “clusters”. They
have also found high indications of positive spatial autocorrelation at the level of the total factor
productivity, which has increased throughout the period of 1960 to 2000. This result could indicate a
tendency to clustering with time.
There is, on the other hand, a variety of studies analysing conditional product convergence
with spatial effects. Armstrong (1995) has defended that the evidence of convergence across European
countries as mentioned by Barro and Sala-i-Martin is due to the omission of spatial autocorrelation in
their analysis and bias resulting from the selection of European regions. Following on, Sandberg
(2004), for example, has examined the hypothesis of absolute and conditional convergence across
Chinese provinces in the period from 1985 to 2000 and found indications that there had been absolute
convergence during the periods of 1985 to 2000 and 1985 to 1990. He has also found evidence that
conditional convergence had been seen in the sub-period of 1990 to 1995, with signs of spatial
dependency across adjacent provinces. Arbia et al. (2004) have studied the convergence of gross
domestic product per capita among 125 regions of 10 European countries from 1985 to 1995,
considering the influence of spatial effects. They concluded that the consideration of spatial
dependency considerably improved the rates of convergence. Lundberg (2004) has tested the
hypothesis of conditional convergence with spatial effects between 1981 and 1990 and, in contrast to
previous results, found no clear evidence favouring the hypothesis of conditional convergence. On the
contrary, the results foresaw conditional divergence across municipalities located in the region of
Stockholm throughout the period and for municipalities outside of the Stockholm region during the
1990s.
This study seeks to test conditional productivity convergence (using as a proxy the product per
worker) for each of the economic sectors of regions (NUTs III) of mainland Portugal from 1995 to
2002, through techniques of cross-section spatial econometrics.
2. Theoretical considerations about convergence with spatial effects
The Neoclassical Theory of absolute (or unconditional) convergence states that poor countries
or regions with low capital/work ratios have a greater marginal productivity of capital and can
therefore grow more than richer countries or regions, given the same level of saving and investment.
In this context, the tendency is for disparities to decrease over a period of time, since there is a
tendency that factor costs will be lower in poorer regions, and, as a result, the opportunities for capital
profit will be higher in these regions in comparison with richer regions. Therefore, less developed
regions attract more investment and tend to grow quicker, thus getting closer to the leading regions. In
the long term, the differences in profit and the rates of growth become equal across regions, since the
existence of free trade and perfect mobility of input encourage convergence. Consequently, in this
theory, convergence to a steady-state is the rule and divergence is a short term transitory phenomenon
which reflects a period of adjustment. Technical progress is exogenous and is treated as a public asset,
freely available to poor regions, thus facilitating the process of imitation and allowing for rapid growth
without the costs of innovation. At an empirical level the Neoclassic approach to absolute convergence
is based on the concept of convergence. The hypothesis of Neoclassic convergence is consistent
with Solow’s exogenous growth model (1956), where growth is determined by the exogenous offer of
inputs, displaying constant profits or scaled decreases.
The concept of convergence measures the dispersion of profit per capita or productivity
across different economies over a period of time and the concept of convergence predicts the
3. inverse relation between profit growth per capita or productivity and its initial level (through cross-
section estimates). The evidence of convergence is useful, since it allows periods of convergence or
divergence over time to be observed. The existence of convergence is different, since it shows the
rate of convergence across countries (regions), and implies that poor countries (regions) grow at a
greater rate than rich countries (regions. The two measurements are complementary, but not
exclusive. convergence is a necessary condition, but not sufficient in itself for there to be
convergence (Sala-i-Martin, 1996). To sum up, the concept of convergence is used more to predict
absolute and conditional convergence. It should also be mentioned that the concept of convergence
was first introduced by Barro and Sala-i-Martin (1991) to distinguish the concept of convergence
which measures, as previously stated, the dispersion of growth per capita using standard deviation or
the coefficient of variation of a particular sample.
More recently, the concept of conditional convergence associated to the Theory of
Endogenous Growth has been introduced. This emphasises the importance of human capital,
innovation and increased profits as conditioning factors of convergence (Barro, 1991). Economies
converge to different steady states which depend on the stock of human capital and the accumulation
of physical capital, among others. This Theory predicts, therefore, a quicker growth for economies
which have not reached their steady state. Empirical studies support that the hypothesis of absolute
convergence is only seen in special cases where the sample involves economies with a high degree of
homogeneity and across regions of the same country. This is known as the “convergence club”
hypothesis (Chatterji, 1992). The majority of studies present results which support the hypothesis of
conditional convergence, where, besides the level of profit per capita or initial productivity, the
accumulation of physical and human capital and the innovation activities were the most significant
conditioning factors. .
The studies which have sought to analyse conditional productivity convergence with spatial
effects, have considered the base model as follows:
p Wp b ln P0 1, conditional productivity convergence, (1)
with spatial effects
where p is rate of growth of sector productivity across various regions, P0 is initial productivity, W is
the matrix of distances, b is the convergence coefficient, is the autoregressive spatial coefficient (of
the spatial lag component) and is the error term (of the spatial error component,
with, W ). The spatial lag and spatial error components are two spatial components which
capture spatial effects in the redundant dependent variable and the error term respectively.
A potential source of errors of specification in spatial econometric models comes from spatial
heterogeneity (Lundberg, 2004). There are typically two aspects related to spatial heterogeneity,
structural instability and heteroskedasticity. Structural instability has to do with the fact that estimated
parameters are not consistent across regions. Heteroskedasticity has to do with errors of specification
which lead to non-constant variances in the error term. To prevent these types of errors of
specification and to test for the existence of spatial lag and spatial error components in models, the
results are generally complemented with specification tests. One of the tests is the Jarque-Bera test
which tests the stability of parameters. The Breuch-Pagan and Koenker-Bassett, in turn, tests for
heteroskedasticity. The second test is the most suitable when normality is rejected by the Jarque-Bera
test. To find out if there are spatial lag and spatial error components in the models, two robust
Lagrange Multiplier tests are used (LME for “spatial error” and LML for “spatial lag”). In brief, the
LME tests the null hypothesis of spatial non-correlation against the alternative of the spatial error
model (“lag”) and LML tests the null hypothesis of spatial non-correlation against the alternative of the
spatial lag model to be the correct specification.
1
Starting from the coefficient of convergence b (1 e T ) it is possible to obtain the rate of convergence
ln(1 b) / T .
4. According to the recommendations of Florax et al. (2003) and using the so-called strategy of
classic specification, the procedure for estimating spatial effects should be carried out in six steps: 1)
Estimate the initial model using the procedures using OLS; 2) Test the hypothesis of spatial non-
dependency due to the omission spatially redundant variables or spatially autoregressive errors, using
the robust tests LME and LML; 3) If none of these tests has statistical significance, opt for the
estimated OLS model, otherwise proceed to the next step, 4) If both tests are significant, opt for spatial
lag or spatial error specifications, whose test has greater significance, otherwise go to step 5;; 5) If
LML is significant while LME is not, use the spatial lag specification; 6) If LME is significant while
LML is not, use the spatial error specification.
A test usually used to indicate the possibility of global spatial autocorrelation is the Moran’s I
test2.
Moran’s I statistics is defined as:
n
w ij ( xi u )( x j u )
I
i j
, Moran’s global autocorrelation test (2)
S (x
i
i u) 2
where n is the number of observations and xi and xj are the observed rates of growth in the locations i
and j (with the average u). S is the constant scale given by the sum of all the distances: S
wij .
i j
When the normalisation of weighting on the lines of the matrix for distances is carried out,
which is preferable, S equals n, since the weighting of each line added up should be equal to the unit,
and the statistical test is compared with its theoretical average, I=-1/(n-1). Then I0, when n. The
null hypothesis H0: I=-1/(n-1) is tested against the alternative hypothesis HA: I-1/(n-1). When H0 is
rejected and I>-1/(n-1) the existence of positive spatial autocorrelation can be verified. That is to say,
the high levels and low levels are more spatially concentrated (clustered) than would be expected
purely by chance. If H0 is rejected once again, but I<-1/(n-1) this indicates negative spatial
autocorrelation.
Moran’s I local autocorrelation test investigates if the values coming from the global
autocorrelation test are significant or not:
xi
Ii w x j , Moran’s local autocorrelation test (3)
xi2
ij
j
i
where the variables signify the same as already referred to by Moran’s I global autocorrelation test.
3. Model of conditional convergence with spatial effects
Bearing in mind the aforementioned theoretical considerations, what is presented next is the
model used to analyse conditional productivity convergence with spatial effects and with human
capital, at a sector and regional level in mainland Portugal:
(1 / T ) log( Pit / Pi 0 ) Wij pit b log Pi 0 X it , with 0 e 0 (4)
In this equation (4) P is sector productivity, p is the rate of growth of sector productivity in
various regions, W is the matrix of distances, X is the vector of variables which represent human
capital (levels of schooling – primary, secondary and higher) b is the convergence coefficient, is
the autoregressive spatial coefficient (of the spatial lag component) and is the error term (of the
spatial error component, with, W ). The indices i, j and t, represent the regions under study,
the neighbouring regions and the period of time respectively.
2
A similar, but less well-known test is Geary’s C test (Sandberg, 2004).
5. 4. Data analysis
The data referring to gross growth value to base prices and employment were obtained in the
Regional Accounts of the National Statistics Institute. To carry out the cross-section estimations, the
GeoDa3 software was used. Also used were data concerning the level of schooling – primary,
secondary or higher education, obtained from the 2001 Census of the National Statistics Institute.
What follows is an analysis of the data, for the product per worker as proxy of the productivity
of work in the period 1995 to 2002 in the various economic sectors of the regions (NUTs III) of
mainland Portugal. The data analysis is carried out while considering, in the various economic sectors,
the values of the productivity ratio of each of the regions under consideration, in relation to average
productivity in mainland Portugal. It also seeks to identify the existence of spatial autocorrelation by
using Moran Scatterplots for over all spatial autocorrelation and LISA Maps for local spatial
autocorrelation.
4.1. Cross-section data analysis
The four Scatterplots, (showing the relation between the growth of productivity and initial
productivity for each of the sectors) presented below, allow for an analysis of productivity
convergence for each of the economic sectors of the Portuguese NUTs III, with average values for the
period 1995 to 2002.
a) Agriculture b) Industry
c) Services d) Total of sectors
Note: PRO = Productivity;
PDE = Initial productivity.
Figure I: Scatterplots of absolute convergence of productivity for each of the economic sectors (cross-section
analysis, 28 regions)
Analysing the four figures above confirms what has been previously shown, or, in other
words, industry is the only economic sector which shows greater tendencies for absolute convergence.
The four Moran Scatterplots (showing the relationship between the dependent variable and the
spatially redundant dependent variable) which are presented below, show Moran’s I statistical values
fro each of the economic sectors and for the total of sectors of the 28 NUTs for mainland Portugal
from 1995 to 2002. The matrix Wij used is the matrix of the distances between the regions up to a
3
Available at http://geodacenter.asu.edu/
6. maximum limit of 97 Km. This distance appeared to be the most appropriate to the reality of
Portuguese NUTs III, given the signs of spatial autocorrelation encountered, (with an analysis of the
data, bearing in mind namely Moran’s I statistics, and with the estimation results carried out) in the
analysis of robustness and behaviour of the various matrices of distance when considering alternative
possibilities of maximum distances. For example, for agriculture and services which, as we shall see,
are the sectors where the signs of autocorrelation are strongest, these indications cease to exist when
the distances are significantly higher than 97 Km. On the other hand, the connectivity of the distance
matrix is weaker for distances over 97 Km. Whatever the case, the choice of the best limiting distance
to construct these matrices is always complex.
a) Agriculture b) Industry
c) Services d) Total of sectors
Note: W-PRO = Spatially redundant productivity;
PRO = Productivity.
Figure II: “Moran Scatterplots” of productivity for each of the economic sectors (cross-section analysis, 28
regions)
An analysis of the Moran Scatterplots shows that it is only in agriculture and services that the
existence of global spatial autocorrelation can be seen in productivity and that there are few
indications of the same occurring in industry, since Moran’s I value is positive..
Figure III analyses the existence of local spatial autocorrelation with four LISA Maps,
investigated under spatial autocorrelation and its significance locally (by NUTs III). The NUTs III
with “high-high” and “low-low” values, correspond to the regions with positive spatial autocorrelation
and with statistical significance, or, in other words, these are cluster regions where the high values
(“high-high”) or low values (“low-low”) of two variables (dependent variable and redundant
dependent variable) are spatially correlated given the existence of spillover effects. The regions with
“high-low” and “low-high” values are “outliers” with negative spatial autocorrelation
7. a) Agriculture b) Industry
c) Services d) Total of sectors
Note:
Figure III: “LISA Cluster Map” of productivity for each of the economic sectors (cross-section analysis, 28
regions)
Analysing the LISA Cluster Maps above confirms what has been verified by the Moran
Scatterplots, or, in other words, the indications of positive spatial autocorrelation are highest in
agriculture and services. Agriculture shows signs of positive spatial correlation with high values in
Greater Lisbon, around Greater Lisbon and the Alentejo and low values in the Centre-North region.
Services present high values for the two variables in the Baixo Alentejo and low values in the region
around Greater Lisbon. There are also some signs of positive spatial autocorrelation in these figures
for industry and the total of sectors, more specifically with high values in some NUTs III of the
Central region. In consideration of what has previously been referred to, spatial spillover effects in
terms of productivity are non-existent in the North and the Algarve. This can be seen with high values
in the Centre for industry and the total of sectors and with low values for agriculture. High values can
be seen in Lisbon and Vale do Tejo for agriculture and low values for services. Positive spatial
autocorrelation in the Alentejo can be seen with high values for agriculture and services. These signs
of positive spatial autocorrelation as described for each of the economic sectors included in various
NUTs III could be an indication of sector similarities in productive structure in each of the strips of
land, given the example of the existence of spatial spillover effects for agriculture in the Alentejo.
5. Conclusions
Considering the analysis of the cross-section data previously carried out, it can be seen that
productivity (product per worker) is subject to positive spatial autocorrelation in agriculture and
services (with Greater Lisbon, curiously, showing the greatest spatial spillover effects in agriculture
than in services). Industry and the total of all sectors also show some signs of spatial autocorrelation.
Also of note is the fact that the region surrounding Lisbon and the Alentejo will clearly have a great
influence in the development of the economy with agriculture. On the other hand, it can be stated that
the tendency for absolute productivity convergence is greatest in industry.
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