Pub Date : 2022-01-01DOI: 10.22394/1993-7601-2022-66-85-98
Bwalya Kalima, T. Gopane
This study examines whether South African unit trust managers can outperform the market and demonstrate distinct market-timing abilities under systematic dynamic risk. A conditional portfolio evaluation method is used under dynamic systematic risk. The BEKK-MGARCH model is applied to estimate the time-varying CAPM beta. The sample of the study includes 86 unit trust funds for the hardly studied multi-asset class between 2010 and 2019 in South Africa. The findings of the study show positive evidence that portfolio managers in the South African unit trust market possess some skills for market timing and outperformance. These results differ from most of the outcomes obtained through model-free performance-evaluation methods. The significant contribution of this study to the literature is in conditioning beta to both time and economic variables within the same asset pricing model, and then applying it to the emerging market of South Africa. Another strength of this paper is maintaining patient and formal adherence to econometric requirements of model validation. The empirical findings of the study should benefit portfolio managers, investors, and regulators with updated insight into the importance of considering both risk variability and changing economic factors in portfolio evaluation.
{"title":"Portfolio performance under dynamic systematic risk and conditional betas: the South African unit trust market","authors":"Bwalya Kalima, T. Gopane","doi":"10.22394/1993-7601-2022-66-85-98","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-66-85-98","url":null,"abstract":"This study examines whether South African unit trust managers can outperform the market and demonstrate distinct market-timing abilities under systematic dynamic risk. A conditional portfolio evaluation method is used under dynamic systematic risk. The BEKK-MGARCH model is applied to estimate the time-varying CAPM beta. The sample of the study includes 86 unit trust funds for the hardly studied multi-asset class between 2010 and 2019 in South Africa. The findings of the study show positive evidence that portfolio managers in the South African unit trust market possess some skills for market timing and outperformance. These results differ from most of the outcomes obtained through model-free performance-evaluation methods. The significant contribution of this study to the literature is in conditioning beta to both time and economic variables within the same asset pricing model, and then applying it to the emerging market of South Africa. Another strength of this paper is maintaining patient and formal adherence to econometric requirements of model validation. The empirical findings of the study should benefit portfolio managers, investors, and regulators with updated insight into the importance of considering both risk variability and changing economic factors in portfolio evaluation.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418380","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-68-5-27
Raphael Amaro, C. Pinho
Changes in commodity prices can be transmitted directly to the real economy through changes in the marginal cost of production. Therefore, it is extremely important to create some mechanism to protect against these movements in the commodities futures market. Exposure in this market comes along with tail risk, which must be measured and controlled using a risk measure. To help economic agents, this research provides a common statistical specification that can be used to reliably predict the Value‐at‐Risk of four important energy commodities. For this, the predictions of a range of 48 competing models, composed of four heteroskedastic specifications, six conditional distributions, and a Markov chain with up to two regimes, were compared using various statistical tests, and the model with the best average results was preferred.
{"title":"Energy commodities: A study on model selection for estimating Value-at-Risk","authors":"Raphael Amaro, C. Pinho","doi":"10.22394/1993-7601-2022-68-5-27","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-68-5-27","url":null,"abstract":"Changes in commodity prices can be transmitted directly to the real economy through changes in the marginal cost of production. Therefore, it is extremely important to create some mechanism to protect against these movements in the commodities futures market. Exposure in this market comes along with tail risk, which must be measured and controlled using a risk measure. To help economic agents, this research provides a common statistical specification that can be used to reliably predict the Value‐at‐Risk of four important energy commodities. For this, the predictions of a range of 48 competing models, composed of four heteroskedastic specifications, six conditional distributions, and a Markov chain with up to two regimes, were compared using various statistical tests, and the model with the best average results was preferred.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68419012","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-68-117-139
S. Dolgikh, B. Potanin
We estimate the effect of higher education on abortion probability in Russia via hierarchical (recursive) probit model with nonrandom selection. To check the robustness of the results modifications of this model accounting for heteroscedasticity and non‐normality of random errors are also applied. We have found statistical evidence that higher education decrease abortion probability. Furthermore, the results of the analysis suggest that there is nonrandom selection into pregnant women and without accounting for it the effect of higher education may be underestimated.
{"title":"Estimating the effect of higher education on abortion","authors":"S. Dolgikh, B. Potanin","doi":"10.22394/1993-7601-2022-68-117-139","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-68-117-139","url":null,"abstract":"We estimate the effect of higher education on abortion probability in Russia via hierarchical (recursive) probit model with nonrandom selection. To check the robustness of the results modifications of this model accounting for heteroscedasticity and non‐normality of random errors are also applied. We have found statistical evidence that higher education decrease abortion probability. Furthermore, the results of the analysis suggest that there is nonrandom selection into pregnant women and without accounting for it the effect of higher education may be underestimated.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418132","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-67-5-26
Yakup Arı
This study focuses on the volatility spillover between the stock prices of foreign banks having business in Turkey and the exchange rate. More particularly, it analyzes the connectedness between the USD-TRY exchange rate volatility and the foreign banks’ stock price volatility in their own country’s stock markets. We select ten foreign banks with the biggest total assets and divide them into two panels: eastern and western capitalized banks. The dataset contains weekly data from 2016-01-04 to 2022-01-17. We estimate volatilities utilizing the Conditional Autoregressive Range (CARR) model and then apply the Time-Varying Parameter- Vector Autoregressive (TVP-VAR) based Diebold–Yilmaz Connectedness Index to reveal the transition and connectedness of volatility. The total connectedness indices show that 26.72 and 54.75% of the forecast error variance originate from other assets included in the spillover analysis for eastern and western panels, respectively. We also explore net pairwise comovements and find that shocks in USD-TRY have dominated on the forecast error variance of bank stocks in the eastern panel, while it is a net volatility receiver in the western panel.
{"title":"The CARR-volatility connectedness between USD/TRY and foreign banks in Turkey: Evidence by TVP-VAR","authors":"Yakup Arı","doi":"10.22394/1993-7601-2022-67-5-26","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-67-5-26","url":null,"abstract":"This study focuses on the volatility spillover between the stock prices of foreign banks having business in Turkey and the exchange rate. More particularly, it analyzes the connectedness between the USD-TRY exchange rate volatility and the foreign banks’ stock price volatility in their own country’s stock markets. We select ten foreign banks with the biggest total assets and divide them into two panels: eastern and western capitalized banks. The dataset contains weekly data from 2016-01-04 to 2022-01-17. We estimate volatilities utilizing the Conditional Autoregressive Range (CARR) model and then apply the Time-Varying Parameter- Vector Autoregressive (TVP-VAR) based Diebold–Yilmaz Connectedness Index to reveal the transition and connectedness of volatility. The total connectedness indices show that 26.72 and 54.75% of the forecast error variance originate from other assets included in the spillover analysis for eastern and western panels, respectively. We also explore net pairwise comovements and find that shocks in USD-TRY have dominated on the forecast error variance of bank stocks in the eastern panel, while it is a net volatility receiver in the western panel.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418566","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-67-27-45
G. Besstremyannaya, Richard B. Dasher, S. Golovan
This paper focuses on innovative manufacturing firms in Japan in 2009–2020 and evaluates differences in the relationship between R&D intensity and firm growth. We use a longitudinal version of the conditional quantile regression model to estimate the augmented Gibrat’s law equation for each of four innovative industries: chemicals and allied products; electronic and other electrical equipment; industrial and commercial machinery and computer equipment; and transportation equipment. The analysis reveals statistical differences in estimated coefficients for R&D intensity across low, median and high-growth firms within each industry and across pairs of industries. The results imply the presence of different patterns of R&D effectiveness which are discussed in the light of R&D management drawing on the experience of Sony and other fast-growing Japanese electronics firms. We also discover heterogeneity in the impact on growth of the age and size of firms.
{"title":"Quantifying heterogeneity in the relationship between R&D intensity and growth at innovative Japanese firms: A quantile regression approach","authors":"G. Besstremyannaya, Richard B. Dasher, S. Golovan","doi":"10.22394/1993-7601-2022-67-27-45","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-67-27-45","url":null,"abstract":"This paper focuses on innovative manufacturing firms in Japan in 2009–2020 and evaluates differences in the relationship between R&D intensity and firm growth. We use a longitudinal version of the conditional quantile regression model to estimate the augmented Gibrat’s law equation for each of four innovative industries: chemicals and allied products; electronic and other electrical equipment; industrial and commercial machinery and computer equipment; and transportation equipment. The analysis reveals statistical differences in estimated coefficients for R&D intensity across low, median and high-growth firms within each industry and across pairs of industries. The results imply the presence of different patterns of R&D effectiveness which are discussed in the light of R&D management drawing on the experience of Sony and other fast-growing Japanese electronics firms. We also discover heterogeneity in the impact on growth of the age and size of firms.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418557","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-65-5-28
E. Bobrovskaya, A. Polbin
In this paper we analyze pricing on a large online platform for short‐term rental housing Airbnb based on Moscow dataset in January 2021. We build a multiple regression model based on a hedonic price function. We identify the main price determinants and the features typical for the specified market. In addition, the results demonstrate the importance of applying quantile regression and geographically weighted regression for more detailed analysis of the determinants of short‐term rental prices.
{"title":"Determinants of short-term rental prices in the sharing economy: The case of Airbnb in Moscow","authors":"E. Bobrovskaya, A. Polbin","doi":"10.22394/1993-7601-2022-65-5-28","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-65-5-28","url":null,"abstract":"In this paper we analyze pricing on a large online platform for short‐term rental housing Airbnb based on Moscow dataset in January 2021. We build a multiple regression model based on a hedonic price function. We identify the main price determinants and the features typical for the specified market. In addition, the results demonstrate the importance of applying quantile regression and geographically weighted regression for more detailed analysis of the determinants of short‐term rental prices.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418261","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-65-77-101
Raphael Amaro, C. Pinho, M. Madaleno
Economic agents need to adequately control, and measure potential financial losses associated with commodity price swings in the futures market. One of the ways to anticipate possible price swings is to measure Value-at-Risk (VaR). In its parametric form, the VaR calculation uses the volatility of a financial asset as a parameter to measure risk. Volatility is the essence of VaR calculation and should be estimated as accurately as possible. The importance of precision in volatility estimation has made heteroskedastic models and their forms of application has evolved significantly in recent years. In this context, this study aimed to verify if the incorporation of several additional parameters in the mathematical expression of the models and the use of different density functions improves the predictive capacity of the conditional variance when used in the measurement of the VaR of the energy commodities in the futures market. The results showed that the use of mathematically more complex structures is not related to better predictions of VaR. However, the use of different density functions allowed the models to fit more adequately to the data, leading to more realistic predictions of conditional variance.
{"title":"Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions","authors":"Raphael Amaro, C. Pinho, M. Madaleno","doi":"10.22394/1993-7601-2022-65-77-101","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-65-77-101","url":null,"abstract":"Economic agents need to adequately control, and measure potential financial losses associated with commodity price swings in the futures market. One of the ways to anticipate possible price swings is to measure Value-at-Risk (VaR). In its parametric form, the VaR calculation uses the volatility of a financial asset as a parameter to measure risk. Volatility is the essence of VaR calculation and should be estimated as accurately as possible. The importance of precision in volatility estimation has made heteroskedastic models and their forms of application has evolved significantly in recent years. In this context, this study aimed to verify if the incorporation of several additional parameters in the mathematical expression of the models and the use of different density functions improves the predictive capacity of the conditional variance when used in the measurement of the VaR of the energy commodities in the futures market. The results showed that the use of mathematically more complex structures is not related to better predictions of VaR. However, the use of different density functions allowed the models to fit more adequately to the data, leading to more realistic predictions of conditional variance.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418428","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-68-50-72
Viktor Lapshin, Anton Markov
This paper investigates how credit rating aggregation might lead to a more efficient estimation of key portfolio risk management metrics: expected credit losses (ECL) and risk‐weighted assets (RWA). The proposed technique for credit rating aggregation is based on the Markov Chain Monte‐Carlo methodology and leads to a statistically smaller variance of ECL and RWA than the naïve and distribution‐based alternatives. This conclusion holds for three public datasets and four simulated studies. The paper results might be helpful for portfolios that suffer from data insufficiency or rely on external ratings for credit risk assessment: portfolios of international companies, interbank loans, and sovereign debt.
{"title":"MCMC-based credit rating aggregation algorithm to tackle data insufficiency","authors":"Viktor Lapshin, Anton Markov","doi":"10.22394/1993-7601-2022-68-50-72","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-68-50-72","url":null,"abstract":"This paper investigates how credit rating aggregation might lead to a more efficient estimation of key portfolio risk management metrics: expected credit losses (ECL) and risk‐weighted assets (RWA). The proposed technique for credit rating aggregation is based on the Markov Chain Monte‐Carlo methodology and leads to a statistically smaller variance of ECL and RWA than the naïve and distribution‐based alternatives. This conclusion holds for three public datasets and four simulated studies. The paper results might be helpful for portfolios that suffer from data insufficiency or rely on external ratings for credit risk assessment: portfolios of international companies, interbank loans, and sovereign debt.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418855","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-65-102-116
Serkan Cahit Dinç, N. Erilli
The Covid-19 which is accepted as a pandemic by the World Health Organisation, has created a global panic effect all over the world. To stop this epidemic, in which more than 4 million people died as of July 2021, researches are being carried out on all kinds of issues related to the disease. In this study, a spatial econometric analysis of the determinants of the total number of Covid-19 cases in the provinces in Turkey between February 8, 2021, and May 7, 2021, was conducted. The existence of spatial autocorrelation was investigated through the Moran I test, and as a result, the Spatial Lagged Model (SAR) was found to be the most appropriate model. According to the results of the spatial analysis, it has been determined that the change in the total number of cases in a province will be in the same direction in the neighboring provinces of that province. A spatial interaction finding was obtained between the provinces and a significant and positive relationship was found between the total number of Covid-19 cases and the population density and the number of people over the age of sixty. Similarly, a significant and negative relationship was found with the average temperature and the total number of healthcare workers, and no significant relationship was found with the literacy rate.
新冠肺炎被世界卫生组织认定为大流行，在世界各地引发了全球恐慌。截至2021年7月，已有400多万人死于这一流行病，为了制止这一流行病，正在对与该疾病有关的各种问题进行研究。在本研究中，对2021年2月8日至2021年5月7日期间土耳其各省Covid-19病例总数的决定因素进行了空间计量经济学分析。通过Moran I检验考察了空间自相关的存在性，发现空间滞后模型(spatial lag Model, SAR)是最合适的模型。根据空间分析的结果，可以确定一个省的病例总数在该省邻近省份的变化方向相同。省域间存在空间交互作用，新冠肺炎病例总数与人口密度、60岁以上人口数量呈显著正相关。同样，与平均气温和医务人员总数呈显著负相关，与识字率无显著相关。
{"title":"Spatial analysis of determinants affecting the total number of Covid-19 cases of provinces in Turkey","authors":"Serkan Cahit Dinç, N. Erilli","doi":"10.22394/1993-7601-2022-65-102-116","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-65-102-116","url":null,"abstract":"The Covid-19 which is accepted as a pandemic by the World Health Organisation, has created a global panic effect all over the world. To stop this epidemic, in which more than 4 million people died as of July 2021, researches are being carried out on all kinds of issues related to the disease. In this study, a spatial econometric analysis of the determinants of the total number of Covid-19 cases in the provinces in Turkey between February 8, 2021, and May 7, 2021, was conducted. The existence of spatial autocorrelation was investigated through the Moran I test, and as a result, the Spatial Lagged Model (SAR) was found to be the most appropriate model. According to the results of the spatial analysis, it has been determined that the change in the total number of cases in a province will be in the same direction in the neighboring provinces of that province. A spatial interaction finding was obtained between the provinces and a significant and positive relationship was found between the total number of Covid-19 cases and the population density and the number of people over the age of sixty. Similarly, a significant and negative relationship was found with the average temperature and the total number of healthcare workers, and no significant relationship was found with the literacy rate.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68417610","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 : 2022-01-01DOI: 10.22394/1993-7601-2022-66-5-24
A. Polbin, A. Skrobotov
The article evaluates cointegrating regression models with time‐varying parameters to describe the relationship between real GDP, gross fixed capital formation and household consumption in the Russian Federation with oil prices. In the early 2000s there was an increase in the elasticities of the analyzed macroeconomic indicators with respect to oil prices, the peak of the elasticities occurred in the second half of the 2000s, after the crisis of 2008–2009 significant declines in elasticities have been identified, and in recent years the oil price elasticity of real GDP has been about 0.05, while for real investment and consumption it has been about 0.12.
{"title":"On decrease in oil price elasticity of GDP and investment in Russia","authors":"A. Polbin, A. Skrobotov","doi":"10.22394/1993-7601-2022-66-5-24","DOIUrl":"https://doi.org/10.22394/1993-7601-2022-66-5-24","url":null,"abstract":"The article evaluates cointegrating regression models with time‐varying parameters to describe the relationship between real GDP, gross fixed capital formation and household consumption in the Russian Federation with oil prices. In the early 2000s there was an increase in the elasticities of the analyzed macroeconomic indicators with respect to oil prices, the peak of the elasticities occurred in the second half of the 2000s, after the crisis of 2008–2009 significant declines in elasticities have been identified, and in recent years the oil price elasticity of real GDP has been about 0.05, while for real investment and consumption it has been about 0.12.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68418296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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