Econometrics: Single Equation Models eJournal最新文献

{"title":"The relationship between price and financial stability in new monetary policy designs: the case of the US using the TVP-SVAR model","authors":"Ömer Yalçinkaya, A. Çelik, Hatıra Sadeghzadeh Emsen","doi":"10.4067/s0718-52862021000200249","DOIUrl":"https://doi.org/10.4067/s0718-52862021000200249","url":null,"abstract":"This study aims to explain the relationship between price and financial stability in monetary policy designs that have developed since the 1990s and to empirically examine the relationship between price and financial stability in the monetary policy designs of the US. To this effect, the study examines the time-varying structure of the relationship between price and financial stability in the US, where monetary policies are designed to achieve price stability, full employment and moderate long-term interest rate targets using the TVP-SVAR model for the period 1993:12-2020:12. The results of the study demonstrate the presence of a reciprocal relationship within the scope of the new environment hypothesis, which varies over time between price and financial stability in the US over the study period. These results broadly suggest the necessity of redesigning monetary policies in the US based on the propositions of the new environment hypothesis and considering the varying structure of the relationships, symmetrical or asymmetrical, between monetary and financial stability variables over time.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125373459","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}

{"title":"Bank Credit and Economic Growth: A Dynamic Threshold Panel Model for ASEAN Countries","authors":"Sy-Hoa Ho, Jamel Saadaoui","doi":"10.2139/ssrn.3861675","DOIUrl":"https://doi.org/10.2139/ssrn.3861675","url":null,"abstract":"While it is widely recognized that the development of a sound financial system may contribute to foster economic growth, the relation between economic growth and financial activities is complex. In this perspective, our contribution investigates the existence of threshold effects in the relationship between economic growth and bank credit. Our sample of ASEAN countries is examined over the period spanning from 1993 to 2019. We use the approach of Kremer et al. (2013) to estimate threshold effects in a dynamic panel where a group of explanatory variables can be endogenous. Our results do not confirm the vanishing effect of finance on economic growth. We found a threshold of 96.5% (significant at the 5% level) for the credit-to-GDP ratio, the threshold variable. In the short run, for observations inferior or equal to the threshold, the positive effect of bank credit expansion on economic growth is around 0.08 (significant at the 1% level). Whereas, for observations superior to the threshold, the positive effect of bank credit expansion on economic growth is around 0.02 (significant at the 1% level). The role of exporting firms is essential in ASEAN countries as they are more export-oriented than other regions in the world economy. Our results may indicate that the beneficiary of the credit (firms versus households), the structural features (export-led growth), and the regional heterogeneity have to be considered in empirical investigations of threshold effects in the relation between economic growth and bank credit. This empirical evidence may help to formulate sound policy recommendations.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127597629","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}

{"title":"The Minimax Estimator of the Average Treatment Effect, among Linear Combinations of Estimators of Bounded Conditional Average Treatment Effects","authors":"Clément de Chaisemartin","doi":"10.2139/ssrn.3846618","DOIUrl":"https://doi.org/10.2139/ssrn.3846618","url":null,"abstract":"I consider estimation of the average treatment effect (ATE), in a population composed of $G$ groups, when one has unbiased and uncorrelated estimators of each group's conditional average treatment effect (CATE). These conditions are met in stratified randomized experiments. I assume that the outcome is homoscedastic, and that each CATE is bounded in absolute value by $B$ standard deviations of the outcome, for some known $B$. I derive, across all linear combinations of the CATEs' estimators, the estimator of the ATE with the lowest worst-case mean-squared error. This minimax-linear estimator assigns a weight equal to group $g$'s share in the population to the most precisely estimated CATEs, and a weight proportional to one over the estimator's variance to the least precisely estimated CATEs. I also derive the minimax-linear estimator when the CATEs' estimators are positively correlated, a condition that may be met by differences-in-differences estimators in staggered adoption designs.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134366679","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}

{"title":"Three Generations of Intergenerational Transmission of Neighbourhood Context","authors":"Lina Hedman, M. van Ham, T. Tammaru","doi":"10.17645/SI.V9I2.3730","DOIUrl":"https://doi.org/10.17645/SI.V9I2.3730","url":null,"abstract":"The literature on intergenerational contextual mobility has shown that neighbourhood status is partly ‘inherited’ from parents by children. Children who spend their childhood in deprived neighbourhoods are more likely to live in such neighbourhoods as adults. It has been suggested that such transmission of neighbourhood status is also relevant from a multiple generation perspective. To our knowledge, however, this has only been confirmed by simulations and not by empirical research. This study uses actual empirical data covering the entire Swedish population over a 25-year period, to investigate intergenerational similarities in neighbourhood status for three generations of Swedish women. The findings suggest that the neighbourhood environments of Swedish women are correlated with the neighbourhood statuses of their mothers and, to some extent, grandmothers. These results are robust over two different analytical strategies—comparing the neighbourhood status of the three generations at roughly similar ages and at the same point in time—and two different spatial scales. We argue that the finding of such effects in (relatively egalitarian) Sweden implies that similar, and possibly stronger, patterns are likely to exist in other countries as well.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125164268","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}

{"title":"A Panel Data Analysis of Stock Returns and Accounting Information in Indian Paint Industry","authors":"Pradeep Kumar Rangi, P. Aithal","doi":"10.47992/IJMTS.2581.6012.0128","DOIUrl":"https://doi.org/10.47992/IJMTS.2581.6012.0128","url":null,"abstract":"The accounting ratios and published financial information serve as a critical tool for investors, creditors, and other stakeholders to ascertain companies' profitability, control, and financial status, which may significantly impact the Stock returns and performance on exchanges. This paper aims to examine whether crucial accounting information affects the price of paint companies in India. In this paper, nine-years (2012-2020) accounting ratios such as returns on asset, equity, and cash cycles for the five listed paint companies in India as explanatory (independent) variables to estimate stock returns. Secondary data is collected chronologically and at a regular yearly frequency. Variables data are derived from the company’s financial statements, Stock Exchange and related website. The study aims to assess and elaborate these accounting ratios effectiveness to substantiate the stock returns of these listed companies. The study uses three-panel data models, the pooled OLS, fixed and random effects, to assess stock returns for the cross-sectional data of these five paint companies. This research indicates that accounting information is significant and positively affects the price of Paint company stock returns on the stock exchange. Both Fixed and Random effect model found to fit the data, significance level of 0.05 (Fixed (FE) at F= 6.3625, p<0.000 and R2 of 0.5462, i.e., fixed effect elaborates for about 55% of the return variance. Random effect at F=10.8647 and p<0.000 and R2 of 0.4429, i.e., elaborates for about 44% of stock return variance. Based on the Hausman data test alternative hypothesis is found to be consistent and therefore Random Effect (RE) model is being used to conclude the findings. The paper's fundamental limitation includes use of limited regressors, companies, and time period. A further qualitative analysis together with other accounting performance indicators as regressors may be included in future studies. These ratios include interest coverage, debt ratios, effective tax rates, asset turnover ratios, dividend distribution ratios, sustainable growth, and top line revenue growth.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"449 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116408531","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}

{"title":"Modeling Long Cycles","authors":"N. Kang, Vadim Marmer","doi":"10.2139/ssrn.3718884","DOIUrl":"https://doi.org/10.2139/ssrn.3718884","url":null,"abstract":"Recurrent boom-and-bust cycles are a salient feature of economic and finan- cial history. Cycles found in the data are stochastic, often highly persistent, and span substantial fractions of the sample size. We refer to such cycles as “long†. In this paper, we develop a novel approach to modeling cyclical behavior specifically designed to capture long cycles. We show that existing inferential procedures may produce misleading results in the presence of long cycles, and propose a new econometric procedure for the inference on the cycle length. Our procedure is asymptotically valid regardless of the cycle length. We apply our methodology to a set of macroeconomic and financial variables for the U.S. We find evidence of long stochastic cycles in the standard business cycle variables, as well as in credit and house prices. However, we rule out the presence of stochastic cycles in asset market data. Moreover, according to our result, financial cycles as characterized by credit and house prices tend to be twice as long as business cycles.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130813054","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}

{"title":"Nonparametric Bounds on Treatment Effects with Imperfect Instruments","authors":"Kyunghoon Ban, Désiré Kédagni","doi":"10.2139/ssrn.3708566","DOIUrl":"https://doi.org/10.2139/ssrn.3708566","url":null,"abstract":"\u0000 This paper extends the identification results in Nevo and Rosen (2012) to nonparametric models. We derive nonparametric bounds on the average treatment effect when an imperfect instrument is available. As in Nevo and Rosen (2012), we assume that the correlation between the imperfect instrument and the unobserved latent variables has the same sign as the correlation between the endogenous variable and the latent variables. We show that the monotone treatment selection and monotone instrumental variable restrictions, introduced by Manski and Pepper (2000, 2009), jointly imply this assumption. Moreover, we show how the monotone treatment response assumption can help tighten the bounds. The identified set can be written in the form of intersection bounds, which is more conducive to inference. We illustrate our methodology using the National Longitudinal Survey of Young Men data to estimate returns to schooling.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"425 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124223190","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}

{"title":"Using and Interpreting Fixed Effects Models","authors":"E. dehaan","doi":"10.2139/ssrn.3699777","DOIUrl":"https://doi.org/10.2139/ssrn.3699777","url":null,"abstract":"Fixed effects are ubiquitous in accounting and finance studies, but many new researchers have only a vague understanding of how they function. This manuscript provides plain-English explanations of how fixed effects can eliminate certain omitted variable biases, affect standard errors, and alter how we should think about sample composition and the interpretation of coefficient estimates. I emphasize that, while fixed effects can be a powerful tool, they can come at the cost of efficiency and can introduce subtle but important econometric problems of their own. Better understanding these issues will help us all make better choices about how to design fixed effects models and carefully interpret the results thereof.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131306794","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}

{"title":"Identification of Causal Direct-Indirect Effects Without Untestable Assumptions","authors":"T. Hoshino","doi":"10.2139/ssrn.3691802","DOIUrl":"https://doi.org/10.2139/ssrn.3691802","url":null,"abstract":"In causal mediation analysis, identification of existing causal direct or indirect effects requires untestable assumptions in which potential outcomes and potential mediators are independent. This paper defines a new causal direct and indirect effect that does not require the untestable assumptions. We show that the proposed measure is identifiable from the observed data, even if potential outcomes and potential mediators are dependent, while the existing natural direct or indirect effects may find a pseudo-indirect effect when the untestable assumptions are violated.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122482481","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}

{"title":"Identification and Estimation of Dynamic Structural Models with Unobserved Choices","authors":"Yingyao Hu, Yi Xin","doi":"10.2139/ssrn.3634910","DOIUrl":"https://doi.org/10.2139/ssrn.3634910","url":null,"abstract":"This paper develops identification and estimation methods for dynamic discrete choice models when agents’ actions are unobserved by econometricians. We provide conditions under which choice probabilities and latent state transition rules are non-parametrically identified with a continuous state variable in a single-agent dynamic discrete choice model. Our identification results extend to models with serially correlated unobserved heterogeneity, cases in which state variables are discrete or choices are partially unavailable, and dynamic discrete games. We propose a sieve maximum likelihood estimator for primitives in agents’ utility functions and state transition rules. Monte Carlo simulation results support the validity of the proposed approach.","PeriodicalId":174229,"journal":{"name":"Econometrics: Single Equation Models eJournal","volume":"620 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123071632","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}