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Includes bibliographical references and index

XVIII, 502 Seiten :

XVIII, 502 Seiten :

XVIII, 502 Seiten :

XVIII, 502 Seiten :

XVIII, 502 Seiten :

XVIII, 502 Seiten :

India’s economy experienced significant transformations between 2001 and 2018, marked by robust GDP growth, fluctuating exchange rates, and varying macroeconomic conditions. This study examines the interactions among key macroeconomic variables, including the exchange rate (ER), real GDP, lending rates, the Index of Industrial Production (IIP), the Consumer Price Index (CPI), and foreign exchange reserves (FER). Utilizing data from this period, the study explores how these variables influence the exchange rate and overall economic stability. The findings highlight the significant impact of inflation and foreign exchange reserves on the exchange rate. A 1% increase in CPI is associated with a 1.027% depreciation of the INR, while a 1% rise in FER leads to a 0.318% appreciation of the currency. These results underscore the importance of effective inflation control measures and strategic management of foreign reserves in maintaining currency stability. The study also discusses the complex interplay between lending rates, industrial production, and economic growth, providing insights for policymakers to ensure sustainable economic development.

India’s economy experienced significant transformations between 2001 and 2018, marked by robust GDP growth, fluctuating exchange rates, and varying macroeconomic conditions. This study examines the interactions among key macroeconomic variables, including the exchange rate (ER), real GDP, lending rates, the Index of Industrial Production (IIP), the Consumer Price Index (CPI), and foreign exchange reserves (FER). Utilizing data from this period, the study explores how these variables influence the exchange rate and overall economic stability. The findings highlight the significant impact of inflation and foreign exchange reserves on the exchange rate. A 1% increase in CPI is associated with a 1.027% depreciation of the INR, while a 1% rise in FER leads to a 0.318% appreciation of the currency. These results underscore the importance of effective inflation control measures and strategic management of foreign reserves in maintaining currency stability. The study also discusses the complex interplay between lending rates, industrial production, and economic growth, providing insights for policymakers to ensure sustainable economic development.

pages cm

pages cm

Abstract A succession of historical events and continuing wars have significantly impacted Yemen's economy, resulting in structural imbalances and a weak monetary system. This research analyses some aspects to determine how these difficulties may affect Yemen's economic stability. The three goals are to evaluate the impact of financial assistance on Yemen's economic recovery, investigate the link between the expansion of the money supply and macroeconomic indicators, and investigate the effects of structural imbalances on living standards and poverty levels. Regression analysis, time-series analysis, and covariance analysis are used in the study to examine the data. The research shows that reducing inflation, financial assistance from Saudi Arabia, and international conventions have considerably helped Yemen's economy become more stable. The research emphasises the urgent requirement for well-coordinated measures to deal with Yemen's economic difficulties. Stakeholders can reduce risk by comprehending these complexities.

Abstract A succession of historical events and continuing wars have significantly impacted Yemen's economy, resulting in structural imbalances and a weak monetary system. This research analyses some aspects to determine how these difficulties may affect Yemen's economic stability. The three goals are to evaluate the impact of financial assistance on Yemen's economic recovery, investigate the link between the expansion of the money supply and macroeconomic indicators, and investigate the effects of structural imbalances on living standards and poverty levels. Regression analysis, time-series analysis, and covariance analysis are used in the study to examine the data. The research shows that reducing inflation, financial assistance from Saudi Arabia, and international conventions have considerably helped Yemen's economy become more stable. The research emphasises the urgent requirement for well-coordinated measures to deal with Yemen's economic difficulties. Stakeholders can reduce risk by comprehending these complexities.

Abstract A succession of historical events and continuing wars have significantly impacted Yemen's economy, resulting in structural imbalances and a weak monetary system. This research analyses some aspects to determine how these difficulties may affect Yemen's economic stability. The three goals are to evaluate the impact of financial assistance on Yemen's economic recovery, investigate the link between the expansion of the money supply and macroeconomic indicators, and investigate the effects of structural imbalances on living standards and poverty levels. Regression analysis, time-series analysis, and covariance analysis are used in the study to examine the data. The research shows that reducing inflation, financial assistance from Saudi Arabia, and international conventions have considerably helped Yemen's economy become more stable. The research emphasises the urgent requirement for well-coordinated measures to deal with Yemen's economic difficulties. Stakeholders can reduce risk by comprehending these complexities.

Click here to view the University of Florida catalog record

Click here to view the University of Florida catalog record

Click here to view the University of Florida catalog record

We propose the use of an angel-daemon framework to perform an uncertainty analysis of short-term macroeconomic models with exogenous components. An uncertainty profile $\mathcal U$ is a short and macroscopic description of a potentially perturbed situation. The angel-daemon framework uses $\mathcal U$ to define a strategic game where two agents, the angel and the daemon, act selfishly having different goals. The Nash equilibria of those games provide the stable strategies in perturbed situations, giving a natural estimation of uncertainty. In this initial work we apply the framework in order to get an uncertainty analysis of linear versions of the IS-LM and the IS-MP models. In those models, by considering uncertainty profiles, we can capture different economical situations. Some of them can be described in terms of macroeconomic policy coordination. In other cases we just analyse the results of the system under some possible perturbation level. Besides providing examples of application we analyse the structure of the Nash equilibria in some particular cases of interest.

This article is from PLoS ONE , volume 9 . Abstract The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelth month, followed by the country risk, with less than 5%.

Includes bibliographical references (pages 167-171) and index

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Lecture 4 of the 2006/2007 UNU-MERIT PhD course on Economic development and innovation studies

Lecture 4 of the 2006/2007 UNU-MERIT PhD course on Economic development and innovation studies

Lecture 4 of the 2006/2007 UNU-MERIT PhD course on Economic development and innovation studies

Lecture 4 of the 2006/2007 UNU-MERIT PhD course on Economic development and innovation studies

Lecture 4 of the 2006/2007 UNU-MERIT PhD course on Economic development and innovation studies

The current study is an effort to empirically assess the effect of various macroeconomic factors on inflation in Pakistan by utilizing ordinary least squares (OLS) method and Granger non-causality test in the time-series framework from 1973-Q3 to 2017-Q2. The empirical results confirm that real GDP, money supply, imports, government expenditure, and lagged inflation have a positive and considerable influence on inflation while interest rate has an adverse impact on inflation. Additionally, the findings demonstrate bidirectional causality between money supply and inflation, while the unidirectional causal relationship is found from government expenditure and imports to inflation. These results signify that inflation does not depend solely on monetary growth in Pakistan; however, imports and fiscal policy are also contributory factors that have a considerable impact on inflation. The study concludes that central authority would not accomplish the stabilize prices through changing the monetary policy until and unless the government will not fix the fiscal deficit.

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Many investigations have used panel methods to study the relationships between fluctuations in economic activity and mortality. A broad consensus has emerged on the overall procyclical nature of mortality: perhaps counter-intuitively, mortality typically rises above its trend during expansions. This consensus has been tarnished by inconsistent reports on the specific age groups and mortality causes involved. We show that these inconsistencies result, in part, from the trend specifications used in previous panel models. A more precise and consistent picture emerges using panel techniques suitable for nonlinear trends. Analyzing data for the 50 US states from 1980 to 2006, we find procyclical mortality in all age groups. We find clear procyclical mortality due to respiratory disease and traffic injuries. Predominantly procyclical cardiovascular disease mortality and countercyclical suicide are subject to substantial state-to-state variation. Neither cancer nor homicide have significant macroeconomic association.

Macroeconomic factors significantly influence a country's economy and financial markets, thereby playing a pivotal role in the development of financial products. The PESTEL framework serves as a comprehensive analytical tool to examine the impact of political, economic, social, technological, environmental, and legal factors in identifying opportunities and threats for financial product development. This study utilizes the PESTEL model to analyze the impact of macroeconomic factors on the evolution of financial products and explores the associated opportunities and challenges. The research investigates macroeconomic factors such as interest rates, inflation, economic growth, political stability, societal changes, technological advancements, growing environmental consciousness, and regulatory frameworks. Data were collected from reliable secondary sources and analyzed using qualitative content analysis. Findings indicate that political stability and government support for financial innovation can foster the development of new products. Conversely, political instability and unexpected regulatory changes pose significant threats to financial firms. Economic conditions like interest rates and economic growth exert a substantial influence on market demand and access to capital. The results suggest that lower interest rates and economic growth create favorable opportunities for financial product development. Furthermore, evolving consumer needs and preferences, coupled with technological advancements, particularly in fintech, are transforming financial processes and customer experiences, enhancing efficiency, and improving customer satisfaction. Additionally, the increasing focus on environmental issues has driven demand for green and sustainable financial products. This research recommends that financial managers and policymakers analyze and understand these factors to capitalize on emerging opportunities and mitigate risks by adapting to environmental and technological changes. Future research can delve deeper into the intricate relationships between these factors through a more international perspective.

Macroeconomic factors significantly influence a country's economy and financial markets, thereby playing a pivotal role in the development of financial products. The PESTEL framework serves as a comprehensive analytical tool to examine the impact of political, economic, social, technological, environmental, and legal factors in identifying opportunities and threats for financial product development. This study utilizes the PESTEL model to analyze the impact of macroeconomic factors on the evolution of financial products and explores the associated opportunities and challenges. The research investigates macroeconomic factors such as interest rates, inflation, economic growth, political stability, societal changes, technological advancements, growing environmental consciousness, and regulatory frameworks. Data were collected from reliable secondary sources and analyzed using qualitative content analysis. Findings indicate that political stability and government support for financial innovation can foster the development of new products. Conversely, political instability and unexpected regulatory changes pose significant threats to financial firms. Economic conditions like interest rates and economic growth exert a substantial influence on market demand and access to capital. The results suggest that lower interest rates and economic growth create favorable opportunities for financial product development. Furthermore, evolving consumer needs and preferences, coupled with technological advancements, particularly in fintech, are transforming financial processes and customer experiences, enhancing efficiency, and improving customer satisfaction. Additionally, the increasing focus on environmental issues has driven demand for green and sustainable financial products. This research recommends that financial managers and policymakers analyze and understand these factors to capitalize on emerging opportunities and mitigate risks by adapting to environmental and technological changes. Future research can delve deeper into the intricate relationships between these factors through a more international perspective.

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Over the last 30 years, the Inforum approach to macro modelling has been shared by economists worldwide. Researchers have focussed much of their efforts to developing a linked system of international interindustry models with a consistent methodology. A world-wide network of research associates use the same methods and software obtaining comparable results. The XXth Inforum World Conference was held in Florence in September 2012 and this book contains a selection of papers presented during that Conference. All these contributions are aimed at policymakers, stakeholders, and applied economists. Some papers are devoted to specific topics (total factor productivity, energy issues, external linkages, demographic changes) and some others are oriented to macro model building and simulations.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.