Pub Date : 2022-10-31DOI: 10.1108/jfep-06-2022-0152
Abdinur Ali Mohamed, M. Nor
Purpose The purpose of this study was to examine the macroeconomic impact of mobile money in Somalia using quarterly data from 2010 to 2020. Design/methodology/approach This study applied the structural vector autoregressive approach to examine the response of the macroeconomic variables to the mobile money shocks. Findings The results show that mobile money increases consumer spending by reducing transaction costs and enhancing access to finance, which promotes the expansion of aggregate output. This study also finds that mobile money helps exchange rate stability and price level maintenance, boosting trade openness. Moreover, mobile money is linked to the rise in real income due to productivity improvement and price stability. The results of this study indicated that mobile money has a short-run relationship with aggregate output, household consumption, price level, trade openness and real income. Through the Granger causality test, this study finds that mobile money has a unidirectional relationship with the exchange rate, price level, household consumption and trade openness. Originality/value The empirical findings of this study imply that mobile money can create a wide range of financial services to improve the financial system in rural and urban areas; hence, it enables poor and rural members of society to make payments and receive-and-transfer money using their mobiles.
{"title":"The macroeconomic impacts of the mobile money: empirical evidence from EVC plus in Somalia","authors":"Abdinur Ali Mohamed, M. Nor","doi":"10.1108/jfep-06-2022-0152","DOIUrl":"https://doi.org/10.1108/jfep-06-2022-0152","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study was to examine the macroeconomic impact of mobile money in Somalia using quarterly data from 2010 to 2020.\u0000\u0000\u0000Design/methodology/approach\u0000This study applied the structural vector autoregressive approach to examine the response of the macroeconomic variables to the mobile money shocks.\u0000\u0000\u0000Findings\u0000The results show that mobile money increases consumer spending by reducing transaction costs and enhancing access to finance, which promotes the expansion of aggregate output. This study also finds that mobile money helps exchange rate stability and price level maintenance, boosting trade openness. Moreover, mobile money is linked to the rise in real income due to productivity improvement and price stability. The results of this study indicated that mobile money has a short-run relationship with aggregate output, household consumption, price level, trade openness and real income. Through the Granger causality test, this study finds that mobile money has a unidirectional relationship with the exchange rate, price level, household consumption and trade openness.\u0000\u0000\u0000Originality/value\u0000The empirical findings of this study imply that mobile money can create a wide range of financial services to improve the financial system in rural and urban areas; hence, it enables poor and rural members of society to make payments and receive-and-transfer money using their mobiles.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62092440","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 : 2022-10-05DOI: 10.1108/jfep-04-2022-0099
Dimitris G. Kirikos
Purpose Advocates of quantitative easing (QE) policies have emphasized some evidence that structural models do not predict long-term asset yields as well as naive forecasts, implying that predictions of price reversals cannot be profitable and that QE effects are not transitory. The purpose of this study is to reconsider the out-of-sample forecasting performance of structural time series processes relative to that of a random walk with or without drift. Design/methodology/approach This study uses bivariate vector autoregression and Markov switching representations to generate out-of-sample forecasts of ten-year sovereign bond yields, when the information set is augmented by including the growth rate of the monetary base, and the estimation relies on monthly data from countries that have pursued unconventional policies over the last decade. Findings The results show that naive forecasts are not better than those of structural time series models, based on root mean squared errors, while the Markov model provides additional information on price reversals, through probabilistic inferences regarding policy regime switches, which can induce agents to counteract QE interventions and reduce their effectiveness. Originality/value The novel features of this work are the use of a large information set including the instrument of unconventional monetary policy, the use of a structural model (Markov process) that can really inform about potential asset price reversals and the use of a large sample over which QE policies have been pursued.
{"title":"Are quantitative easing effects transitory? Evidence from out-of-sample forecasts","authors":"Dimitris G. Kirikos","doi":"10.1108/jfep-04-2022-0099","DOIUrl":"https://doi.org/10.1108/jfep-04-2022-0099","url":null,"abstract":"\u0000Purpose\u0000Advocates of quantitative easing (QE) policies have emphasized some evidence that structural models do not predict long-term asset yields as well as naive forecasts, implying that predictions of price reversals cannot be profitable and that QE effects are not transitory. The purpose of this study is to reconsider the out-of-sample forecasting performance of structural time series processes relative to that of a random walk with or without drift.\u0000\u0000\u0000Design/methodology/approach\u0000This study uses bivariate vector autoregression and Markov switching representations to generate out-of-sample forecasts of ten-year sovereign bond yields, when the information set is augmented by including the growth rate of the monetary base, and the estimation relies on monthly data from countries that have pursued unconventional policies over the last decade.\u0000\u0000\u0000Findings\u0000The results show that naive forecasts are not better than those of structural time series models, based on root mean squared errors, while the Markov model provides additional information on price reversals, through probabilistic inferences regarding policy regime switches, which can induce agents to counteract QE interventions and reduce their effectiveness.\u0000\u0000\u0000Originality/value\u0000The novel features of this work are the use of a large information set including the instrument of unconventional monetary policy, the use of a structural model (Markov process) that can really inform about potential asset price reversals and the use of a large sample over which QE policies have been pursued.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46751701","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 : 2022-08-18DOI: 10.1108/jfep-07-2022-0175
Matthew S. Flynn, Yufei Wu
Purpose This study aims to provide a fresh look at banks as lenders in and extending past the COVID-19 crisis, with a particular focus on examining the results of recent work by Lei et al. (2020). Design/methodology/approach The authors’ replication, as well as the original paper, uses a fixed-effects model on panel data. The authors discuss issues regarding data sources as well as use an array of panel data robustness checks to help ascertain an appropriate empirical specification for continued research of this type. Findings The authors show that the results of Lei et al. (2020) are sensitive to the data source, as well as the construction of the standard errors in their regression framework, with an appropriate specification uncovered through panel data statistical tests. The authors also provide some extensions to the original work by including interacted fixed-effects models and extending the sample period from 2020Q1 to 2021Q1, noting some changes in results. Originality/value The authors provide novel results on banks’ lending constraints both at the onset of the COVID-19 pandemic and shortly thereafter. The study also provides an empirical framework for future studies conducted on similar panel data sets.
{"title":"Another look at banks as lenders of first resort: evidence from the COVID-19 crisis","authors":"Matthew S. Flynn, Yufei Wu","doi":"10.1108/jfep-07-2022-0175","DOIUrl":"https://doi.org/10.1108/jfep-07-2022-0175","url":null,"abstract":"\u0000Purpose\u0000This study aims to provide a fresh look at banks as lenders in and extending past the COVID-19 crisis, with a particular focus on examining the results of recent work by Lei et al. (2020).\u0000\u0000\u0000Design/methodology/approach\u0000The authors’ replication, as well as the original paper, uses a fixed-effects model on panel data. The authors discuss issues regarding data sources as well as use an array of panel data robustness checks to help ascertain an appropriate empirical specification for continued research of this type.\u0000\u0000\u0000Findings\u0000The authors show that the results of Lei et al. (2020) are sensitive to the data source, as well as the construction of the standard errors in their regression framework, with an appropriate specification uncovered through panel data statistical tests. The authors also provide some extensions to the original work by including interacted fixed-effects models and extending the sample period from 2020Q1 to 2021Q1, noting some changes in results.\u0000\u0000\u0000Originality/value\u0000The authors provide novel results on banks’ lending constraints both at the onset of the COVID-19 pandemic and shortly thereafter. The study also provides an empirical framework for future studies conducted on similar panel data sets.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43388158","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 : 2022-08-04DOI: 10.1108/jfep-04-2022-0091
Alya Al-Fori, Azmat Gani
Purpose Islamic finance is becoming a core part of the financial services economy in the Middle East countries. There is a strong likelihood that Islamic finance is also driving the expansion of trade in insurance services. However, research on Islamic finance’s effect on trade in insurance services is scant. This study aims to fill this gap by investigating if Islamic finance has promoted trade in insurance services. Design/methodology/approach This study adopts the gravity modelling framework and the panel data estimation procedure in understanding the effects of Islamic finance on trade in insurance. Findings The empirical results reveal a statistically significant positive correlation of Islamic finance with the exports and imports of insurance services. Economic sizes (domestic and trading partners), growth in trading partners, cost of doing business, legal rights and financial freedom are other statistically significant determinants. Research limitations/implications It makes a positive contribution to the Islamic financial services literature. Islamic finance is an integral part of the conventional banking and financial sector in the Middle East that actively fosters the expansion of insurance services that need support, given its essential role in services trade. Originality/value This study is unique as it directs attention to the role of Islamic finance in fostering trade in insurance services within an inclusive modelling framework that has been overlooked in the Islamic finance literature.
{"title":"The effect of Islamic finance on trade in insurance services in selected countries in the Middle East region","authors":"Alya Al-Fori, Azmat Gani","doi":"10.1108/jfep-04-2022-0091","DOIUrl":"https://doi.org/10.1108/jfep-04-2022-0091","url":null,"abstract":"\u0000Purpose\u0000Islamic finance is becoming a core part of the financial services economy in the Middle East countries. There is a strong likelihood that Islamic finance is also driving the expansion of trade in insurance services. However, research on Islamic finance’s effect on trade in insurance services is scant. This study aims to fill this gap by investigating if Islamic finance has promoted trade in insurance services.\u0000\u0000\u0000Design/methodology/approach\u0000This study adopts the gravity modelling framework and the panel data estimation procedure in understanding the effects of Islamic finance on trade in insurance.\u0000\u0000\u0000Findings\u0000The empirical results reveal a statistically significant positive correlation of Islamic finance with the exports and imports of insurance services. Economic sizes (domestic and trading partners), growth in trading partners, cost of doing business, legal rights and financial freedom are other statistically significant determinants.\u0000\u0000\u0000Research limitations/implications\u0000It makes a positive contribution to the Islamic financial services literature. Islamic finance is an integral part of the conventional banking and financial sector in the Middle East that actively fosters the expansion of insurance services that need support, given its essential role in services trade.\u0000\u0000\u0000Originality/value\u0000This study is unique as it directs attention to the role of Islamic finance in fostering trade in insurance services within an inclusive modelling framework that has been overlooked in the Islamic finance literature.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49612126","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 : 2022-05-12DOI: 10.1108/jfep-04-2022-0090
G. J. Jolley
Purpose This paper aims to estimate the economic impact of a basic income for each state in the USA. Design/methodology/approach Building on existing pilot studies of basic income in the USA, this paper presumes a $500 per month basic income for individuals earning less than $25,000 in annual income. Using impact analysis for planning (IMPLAN) input–output modeling software, estimated increase in gross state product and employment are provided on a state-by-state basis. Findings A $6,000 annual basic income ($500 per month) to adult persons earning less than $25,000 annually results in an increase in gross state product (e.g. gross “regional” product in IMPLAN terminology) ranging from 0.7% (District of Columbia) to 5.7% (Florida). Likewise, this increase in household spending will create demand for employment across these states, resulting in an increase in employment from 0.9% (District of Columbia) to 5.8% (Florida). Originality/value To date, to the best of the author’s knowledge, this is the first state-by-state analysis of the economic impact of a basic income provision to lower-income individuals.
{"title":"Basic income: a 50-state economic impact analysis","authors":"G. J. Jolley","doi":"10.1108/jfep-04-2022-0090","DOIUrl":"https://doi.org/10.1108/jfep-04-2022-0090","url":null,"abstract":"\u0000Purpose\u0000This paper aims to estimate the economic impact of a basic income for each state in the USA.\u0000\u0000\u0000Design/methodology/approach\u0000Building on existing pilot studies of basic income in the USA, this paper presumes a $500 per month basic income for individuals earning less than $25,000 in annual income. Using impact analysis for planning (IMPLAN) input–output modeling software, estimated increase in gross state product and employment are provided on a state-by-state basis.\u0000\u0000\u0000Findings\u0000A $6,000 annual basic income ($500 per month) to adult persons earning less than $25,000 annually results in an increase in gross state product (e.g. gross “regional” product in IMPLAN terminology) ranging from 0.7% (District of Columbia) to 5.7% (Florida). Likewise, this increase in household spending will create demand for employment across these states, resulting in an increase in employment from 0.9% (District of Columbia) to 5.8% (Florida).\u0000\u0000\u0000Originality/value\u0000To date, to the best of the author’s knowledge, this is the first state-by-state analysis of the economic impact of a basic income provision to lower-income individuals.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44634041","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 : 2022-05-09DOI: 10.1108/jfep-03-2022-0080
R. Cebula, Maggie Foley
Purpose The purpose of this analysis is to explain why labor shortages may have appeared during this pandemic. Interestingly, in this COVID-19 pandemic period, the labor supply shortage could very well become more easily explained than under the traditional portrayal of consumer economic behavior. The matter seemingly lends itself to provocative empirical inquiry. Design/methodology/approach From this model, it can be shown that the consumer’s labor supply curve is negatively sloped and, indeed, could even assume the form of a rectangular hyperbola. Applying this model in the labor market could explain the labor shortage in the USA during the COVID-19 pandemic. Findings Arguably, rational consumer behavior can take the form, under a variety of circumstances (including cultural), for consumers/households that have achieved a “comfortable” standing of living/utility level, involve the minimization of work effort to achieve that utility level. In other words, constrained utility maximization is not the only rational form of consumer economic behavior. When the former behavior prevails over the latter, there are myriad implications. These do include an inverse relationship between work effort and wage rate, i.e. a negatively sloped labor supply curve. Originality/value This paper departs from the conventional treatment of deriving the supply curve of labor based on constrained utility maximization. Instead, it acknowledges that consumers may have a target standard of living and seek to minimize the cost of achieving that given living standard.
{"title":"Labor shortages during the COVID-19 and labor supply based on minimizing effort to achieve a target utility level: confounding economic policies","authors":"R. Cebula, Maggie Foley","doi":"10.1108/jfep-03-2022-0080","DOIUrl":"https://doi.org/10.1108/jfep-03-2022-0080","url":null,"abstract":"\u0000Purpose\u0000The purpose of this analysis is to explain why labor shortages may have appeared during this pandemic. Interestingly, in this COVID-19 pandemic period, the labor supply shortage could very well become more easily explained than under the traditional portrayal of consumer economic behavior. The matter seemingly lends itself to provocative empirical inquiry.\u0000\u0000\u0000Design/methodology/approach\u0000From this model, it can be shown that the consumer’s labor supply curve is negatively sloped and, indeed, could even assume the form of a rectangular hyperbola. Applying this model in the labor market could explain the labor shortage in the USA during the COVID-19 pandemic.\u0000\u0000\u0000Findings\u0000Arguably, rational consumer behavior can take the form, under a variety of circumstances (including cultural), for consumers/households that have achieved a “comfortable” standing of living/utility level, involve the minimization of work effort to achieve that utility level. In other words, constrained utility maximization is not the only rational form of consumer economic behavior. When the former behavior prevails over the latter, there are myriad implications. These do include an inverse relationship between work effort and wage rate, i.e. a negatively sloped labor supply curve.\u0000\u0000\u0000Originality/value\u0000This paper departs from the conventional treatment of deriving the supply curve of labor based on constrained utility maximization. Instead, it acknowledges that consumers may have a target standard of living and seek to minimize the cost of achieving that given living standard.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48665237","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 : 2022-04-25DOI: 10.1108/jfep-01-2022-0001
Anwar Hasan Abdullah Othman, Mohamed Alshami, Adam Abdullah
Purpose This paper aims to investigate the linear and nonlinear interactions between the blockchain technology index and the UAE stock market index within the context of the Abu Dhabi and Dubai banking sector. Design/methodology/approach In this study, linear analysis was performed using the generalized autoregressive conditional heteroscedasticity model (GARCH) (1,1) model, whereas nonlinear analysis was performed using the wavelet coherence model. Findings Based on the results of the GARCH (1) model, the authors find that the blockchain technology index has a positive significant impact on stock market returns in the Abu Dhabi and Dubai banking sector. In addition, the findings indicate that increasing blockchain integration in the banking industry decreases banks’ stock market volatility and facilitates price stabilization. Additionally, the coherence wavelet analysis reveals that there is a phase relationship between the blockchain technology index and banks’ stock market indices in the banking sector of the UAE. The association was stronger during the global pandemic crisis because they were moving together across different timescales. Practical implications With the help of the linear analysis, this study offers a focal point and valuable insights to policymakers, central banks and commercial banks management on how implementing blockchain technology in the banking industry help boost stock market returns, reduce volatility and facilitate price stability. As a result of the nonlinear analysis of the significant long-term degree of co-movement between blockchain technology and banks’ stock markets in UAE, policymakers or the management of banks in UAE should take the growth of the blockchain technology industry into consideration to ensure the continued development of the banking sector. For investors, the findings provide implications for portfolio managers operating in the UAE who are encouraged to take short-term co-movement into account (1–16-week horizons) through both frequency and time when designing their portfolio while keeping long-horizon periods in mind is not recommended. Originality/value It is a pioneering study that empirically examines the linear and nonlinear nexus between the blockchain technology index and banks’ stock market returns and price stability.
{"title":"The linear and non-linear interactions between blockchain technology index and the stock market indices: a case study of the UAE banking sector","authors":"Anwar Hasan Abdullah Othman, Mohamed Alshami, Adam Abdullah","doi":"10.1108/jfep-01-2022-0001","DOIUrl":"https://doi.org/10.1108/jfep-01-2022-0001","url":null,"abstract":"\u0000Purpose\u0000This paper aims to investigate the linear and nonlinear interactions between the blockchain technology index and the UAE stock market index within the context of the Abu Dhabi and Dubai banking sector.\u0000\u0000\u0000Design/methodology/approach\u0000In this study, linear analysis was performed using the generalized autoregressive conditional heteroscedasticity model (GARCH) (1,1) model, whereas nonlinear analysis was performed using the wavelet coherence model.\u0000\u0000\u0000Findings\u0000Based on the results of the GARCH (1) model, the authors find that the blockchain technology index has a positive significant impact on stock market returns in the Abu Dhabi and Dubai banking sector. In addition, the findings indicate that increasing blockchain integration in the banking industry decreases banks’ stock market volatility and facilitates price stabilization. Additionally, the coherence wavelet analysis reveals that there is a phase relationship between the blockchain technology index and banks’ stock market indices in the banking sector of the UAE. The association was stronger during the global pandemic crisis because they were moving together across different timescales.\u0000\u0000\u0000Practical implications\u0000With the help of the linear analysis, this study offers a focal point and valuable insights to policymakers, central banks and commercial banks management on how implementing blockchain technology in the banking industry help boost stock market returns, reduce volatility and facilitate price stability. As a result of the nonlinear analysis of the significant long-term degree of co-movement between blockchain technology and banks’ stock markets in UAE, policymakers or the management of banks in UAE should take the growth of the blockchain technology industry into consideration to ensure the continued development of the banking sector. For investors, the findings provide implications for portfolio managers operating in the UAE who are encouraged to take short-term co-movement into account (1–16-week horizons) through both frequency and time when designing their portfolio while keeping long-horizon periods in mind is not recommended.\u0000\u0000\u0000Originality/value\u0000It is a pioneering study that empirically examines the linear and nonlinear nexus between the blockchain technology index and banks’ stock market returns and price stability.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48730440","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 : 2022-04-05DOI: 10.1108/jfep-06-2021-0162
Mallika Saha, Kumar Debasis Dutta
Purpose This paper aims to investigate the debated nexus of financial inclusion (FI) and financial stability (FS) in a comprehensive way, with several indicators of FI, considering nonlinearity and cross-country heterogeneity. Design/methodology/approach The authors introduce several indexes for FI by applying principal component analysis (PCA) and explore their impact on stability for a sample of 108 countries and subsamples based on income grouping as well as for pre- and post-crisis episodes over the period 2004–2017. To address the heterogeneity and endogeneity, the authors use the two-step quantile regression (2SQR), three-stage least square (3SLS) and two-step system-GMM (System-GMM). Findings The findings reveal that the relationship of FI and stability depends on the measurement of FI used and the heterogeneity of different macroeconomic factors. Besides, there is nonlinearity, irrespective of the measurement of inclusion used. The findings also confirm that the effect of FI is more prominent in countries with strong governance. The results are robust to several robustness validations, which could be useful for policymakers to align the divergence of these policies and ensure FS while expanding access to formal financial services. Originality/value This study makes an attempt to explore the reasons behind the debated empirical findings of the existing literature by revisiting the nexus using several disaggregated indexes, each representing individual dimension and a multidimensional index, examine the possible nonlinearity and investigate the conditioning effect of different macroeconomic factors that might play a significant role in this relationship.
{"title":"Revisiting financial inclusion-stability nexus: cross-country heterogeneity","authors":"Mallika Saha, Kumar Debasis Dutta","doi":"10.1108/jfep-06-2021-0162","DOIUrl":"https://doi.org/10.1108/jfep-06-2021-0162","url":null,"abstract":"\u0000Purpose\u0000This paper aims to investigate the debated nexus of financial inclusion (FI) and financial stability (FS) in a comprehensive way, with several indicators of FI, considering nonlinearity and cross-country heterogeneity.\u0000\u0000\u0000Design/methodology/approach\u0000The authors introduce several indexes for FI by applying principal component analysis (PCA) and explore their impact on stability for a sample of 108 countries and subsamples based on income grouping as well as for pre- and post-crisis episodes over the period 2004–2017. To address the heterogeneity and endogeneity, the authors use the two-step quantile regression (2SQR), three-stage least square (3SLS) and two-step system-GMM (System-GMM).\u0000\u0000\u0000Findings\u0000The findings reveal that the relationship of FI and stability depends on the measurement of FI used and the heterogeneity of different macroeconomic factors. Besides, there is nonlinearity, irrespective of the measurement of inclusion used. The findings also confirm that the effect of FI is more prominent in countries with strong governance. The results are robust to several robustness validations, which could be useful for policymakers to align the divergence of these policies and ensure FS while expanding access to formal financial services.\u0000\u0000\u0000Originality/value\u0000This study makes an attempt to explore the reasons behind the debated empirical findings of the existing literature by revisiting the nexus using several disaggregated indexes, each representing individual dimension and a multidimensional index, examine the possible nonlinearity and investigate the conditioning effect of different macroeconomic factors that might play a significant role in this relationship.\u0000","PeriodicalId":45556,"journal":{"name":"Journal of Financial Economic Policy","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42205560","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 : 2022-04-04DOI: 10.1108/jfep-02-2022-0039
Puneet Vatsa, F. Mixon
Purpose This paper aims to investigate the cyclical associations among energy prices and key macroeconomic variables for the USA. Design/methodology/approach To this end, the recently developed Hamilton filter (HF) and the oft-used Hodrick–Prescott filter (HPF) are used. The two methods produce starkly different results regarding the relationships between energy prices on the one hand and output and employment on the other. Findings While the HF suggests that energy prices are acyclical, the HPF suggests they are procyclical. However, the associations between energy prices and inflation are robust across the two methods, indicating that energy prices are strongly correlated with – and lead – the consumer price index (CPI). Furthermore, unlike the results produced by the HPF, those produced by the HF are robust across seasonally adjusted and unadjusted data. Research limitations/implications Given the inherent seasonality in energy prices and the differences in the underlying processes that generate macroeconomic and energy prices, the results obtained from the HPF filter should be interpreted with caution. Originality/value To the best of the authors’ knowledge, this is the first study that uses the recently developed HF to examine the associations between the cyclical behaviors of three key macroeconomic variables in the USA – the industrial production index, the CPI, and total nonfarm employment – and the prices of natural gas, crude oil, gasoline, diesel, and heating oil. Second, this study presents a comparison of the results produced by the two filtering techniques. Third, recognizing that energy prices are characterized by seasonality, this study tests the robustness of the results produced by the two filters across seasonally adjusted and unadjusted data.
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Pub Date : 2022-03-14DOI: 10.1108/jfep-08-2021-0206
Y. A. Sare, E. Davies, Joseph Dery Nyeadi
Purpose This study purposely re‐examine the mortgage–finance nexus in Africa. Design/methodology/approach This study adopted a panel data set spanning over the period 1995–2017 by using system generalized method of moments (GMM) dynamic pooled estimator developed by Arellano and Bond (1991) and Arellano and Bover (1995) involving 51 African countries. Findings The findings discovered that financial development (bank asset) affects mortgage development positively and this effect is highly significant while broad money supply as a measure of financial development impedes mortgage development in Africa. Furthermore, with the introduction of the quadratic term, broad money supply established a U-shaped relationship with mortgage financing indicating that more money in circulation facilitates mortgage development in Africa. However, the shape of the other variables depends largely on the nature of proxy used. Originality/value This study is unique in many aspects. First, examining the extant literature on the financial development and mortgage financing nexus, to the best of the authors’ knowledge, no study is cited at the African level with this relationship. Secondly is the empirical model, as it used the system GMM dynamic pooled estimator developed by Arellano and Bond (1991) and Arellano and Bover (1995) to establish whether there is any effect of finance–mortgage nexus.
目的本研究有意重新审视非洲的抵押贷款与融资关系。设计/方法/方法本研究采用了一个涵盖1995-2017年的面板数据集，使用了Arellano和Bond（1991）以及Arellano and Bover（1995）开发的系统广义矩量法（GMM）动态集合估计量，涉及51个非洲国家。研究结果发现，金融发展（银行资产）对抵押贷款发展有积极影响，这种影响非常显著，而作为衡量金融发展的指标的广义货币供应阻碍了非洲的抵押贷款发展。此外，随着二次项的引入，广义货币供应量与抵押贷款融资建立了U型关系，这表明更多的货币流通促进了非洲抵押贷款的发展。然而，其他变量的形状在很大程度上取决于所使用代理的性质。独创性/价值这项研究在许多方面都是独一无二的。首先，根据作者所知，在研究金融发展和抵押贷款融资关系的现有文献时，没有在非洲层面引用任何与这种关系有关的研究。其次是经验模型，因为它使用了由Arellano和Bond（1991）以及Arellano and Bover（1995）开发的系统GMM动态集合估计器来确定是否存在金融-抵押关系的任何影响。
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