Jorge Martínez Compains, Ignacio Rodríguez Carreño, R. Gencay, Tommaso Trani, Daniel Ramos Vilardell
Abstract Johansen’s Cointegration Test (JCT) performs remarkably well in finding stable bivariate cointegration relationships. Nonetheless, the JCT is not necessarily designed to detect such relationships in presence of non-linear patterns such as structural breaks or cycles that fall in the low frequency portion of the spectrum. Seasonal adjustment procedures might not detect such non-linear patterns, and thus, we expose the difficulty in identifying cointegrating relations under the traditional use of JCT. Within several Monte Carlo experiments, we show that wavelets can empower more the JCT framework than the traditional seasonal adjustment methodologies, allowing for identification of hidden cointegrating relationships. Moreover, we confirm these results using seasonally adjusted time series as US consumption and income, gross national product (GNP) and money supply M1 and GNP and M2.
{"title":"Recovering cointegration via wavelets in the presence of non-linear patterns","authors":"Jorge Martínez Compains, Ignacio Rodríguez Carreño, R. Gencay, Tommaso Trani, Daniel Ramos Vilardell","doi":"10.1515/snde-2018-0120","DOIUrl":"https://doi.org/10.1515/snde-2018-0120","url":null,"abstract":"Abstract Johansen’s Cointegration Test (JCT) performs remarkably well in finding stable bivariate cointegration relationships. Nonetheless, the JCT is not necessarily designed to detect such relationships in presence of non-linear patterns such as structural breaks or cycles that fall in the low frequency portion of the spectrum. Seasonal adjustment procedures might not detect such non-linear patterns, and thus, we expose the difficulty in identifying cointegrating relations under the traditional use of JCT. Within several Monte Carlo experiments, we show that wavelets can empower more the JCT framework than the traditional seasonal adjustment methodologies, allowing for identification of hidden cointegrating relationships. Moreover, we confirm these results using seasonally adjusted time series as US consumption and income, gross national product (GNP) and money supply M1 and GNP and M2.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"255 - 265"},"PeriodicalIF":0.8,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46936286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Although the prediction of stock prices and analyses of their returns and risks have always played integral roles in the stock market, accurate predictions are notoriously difficult to make, and mistakes may be devastatingly costly. This study attempts to resolve this difficulty by proposing and applying a two-stage long short-term memory (LSTM) model based on multi-scale nonlinear integration that considers a diverse array of factors. Initially, variational mode decomposition (VMD) is used to decompose an employed stock index to identify the different characteristics of the stock index sequence. Then, an LSTM model based on the multi-factor nonlinear integration of overnight information is established in a second stage. Finally, the joint VMD-LSTM model is used to predict the stock index. To validate the model, the Shanghai Composite, Nikkei 225, and Hong Kong Hang Seng indices were analyzed. Experiments show that, by comparison, the prediction effect of the mixed model is better than that of a single LSTM. For example, RMSE, MAE and MAPE of the mixed model of the Shanghai Composite Index are 4.22, 4.25 and 0.2 lower than the single model respectively. The RMSE, MAE and MAPE of the mixed model of the Nikkei 225 Index are 47.74, 37.21 and 0.17 lower than the single model respectively, and the RMSE, MAE and MAPE of the mixed model of the Hong Kong Hang Seng Index are 37.88, 25.06 and 0.08 lower than the single model respectively.
{"title":"Prediction of stock index of two-scale long short-term memory model based on multiscale nonlinear integration","authors":"Decai Tang, Zhiwei Pan, Brandon J. Bethel","doi":"10.1515/snde-2021-0032","DOIUrl":"https://doi.org/10.1515/snde-2021-0032","url":null,"abstract":"Abstract Although the prediction of stock prices and analyses of their returns and risks have always played integral roles in the stock market, accurate predictions are notoriously difficult to make, and mistakes may be devastatingly costly. This study attempts to resolve this difficulty by proposing and applying a two-stage long short-term memory (LSTM) model based on multi-scale nonlinear integration that considers a diverse array of factors. Initially, variational mode decomposition (VMD) is used to decompose an employed stock index to identify the different characteristics of the stock index sequence. Then, an LSTM model based on the multi-factor nonlinear integration of overnight information is established in a second stage. Finally, the joint VMD-LSTM model is used to predict the stock index. To validate the model, the Shanghai Composite, Nikkei 225, and Hong Kong Hang Seng indices were analyzed. Experiments show that, by comparison, the prediction effect of the mixed model is better than that of a single LSTM. For example, RMSE, MAE and MAPE of the mixed model of the Shanghai Composite Index are 4.22, 4.25 and 0.2 lower than the single model respectively. The RMSE, MAE and MAPE of the mixed model of the Nikkei 225 Index are 47.74, 37.21 and 0.17 lower than the single model respectively, and the RMSE, MAE and MAPE of the mixed model of the Hong Kong Hang Seng Index are 37.88, 25.06 and 0.08 lower than the single model respectively.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"723 - 735"},"PeriodicalIF":0.8,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49175425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This paper empirically examines the long-run relationship between consumption, asset wealth and labor income (i.e., cay) in the United States through the lens of a quantile cointegration approach. The advantage of using this approach is that it allows for a nonlinear relationship between these variables depending on the level of consumption. We estimate the coefficients using a Phillips–Hansen type fully modified quantile estimator to correct for the presence of endogeneity in the cointegrating relationship. To test for the null of cointegration at each quantile, we apply a quantile CUSUM test. Results show that: (i) consumption is more sensitive to changes in labor income than to changes in asset wealth for the entire distribution of consumption, (ii) the elasticity of consumption with respect to labor income (asset wealth) is larger at the right (left) tail of the consumption distribution than at the left (right) tail, (iii) the series are cointegrated around the median, but not in the tails of the distribution of consumption, (iv) using the estimated cay obtained for the right (left) tail of the distribution of consumption improves the long-run (short-run) forecast ability on real excess stock returns over a risk-free rate.
{"title":"Consumption, aggregate wealth and expected stock returns: a quantile cointegration approach","authors":"Ricardo Quineche","doi":"10.1515/snde-2020-0059","DOIUrl":"https://doi.org/10.1515/snde-2020-0059","url":null,"abstract":"Abstract This paper empirically examines the long-run relationship between consumption, asset wealth and labor income (i.e., cay) in the United States through the lens of a quantile cointegration approach. The advantage of using this approach is that it allows for a nonlinear relationship between these variables depending on the level of consumption. We estimate the coefficients using a Phillips–Hansen type fully modified quantile estimator to correct for the presence of endogeneity in the cointegrating relationship. To test for the null of cointegration at each quantile, we apply a quantile CUSUM test. Results show that: (i) consumption is more sensitive to changes in labor income than to changes in asset wealth for the entire distribution of consumption, (ii) the elasticity of consumption with respect to labor income (asset wealth) is larger at the right (left) tail of the consumption distribution than at the left (right) tail, (iii) the series are cointegrated around the median, but not in the tails of the distribution of consumption, (iv) using the estimated cay obtained for the right (left) tail of the distribution of consumption improves the long-run (short-run) forecast ability on real excess stock returns over a risk-free rate.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"693 - 703"},"PeriodicalIF":0.8,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44916808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In this paper multivariate State Space (SS) models are used to evaluate and forecast household loans in Brazil, taking into account two Google search terms in order to identify credit demand: financiamento (type of loan used to finance goods) and empréstimo (a more general type of loan). Our framework is coupled with nonlinear features, such as Markov-switching and threshold point. We explore these nonlinearities to build identification strategies to disentangle the supply and demand forces which drive the credit market to equilibrium over time. We also show that the underlying nonlinearities significantly improves the performance of SS models on forecasting the household loans in Brazil, particularly in short-term horizons.
{"title":"What does Google say about credit developments in Brazil?","authors":"A. Neto, Osvaldo Candido","doi":"10.1515/snde-2019-0122","DOIUrl":"https://doi.org/10.1515/snde-2019-0122","url":null,"abstract":"Abstract In this paper multivariate State Space (SS) models are used to evaluate and forecast household loans in Brazil, taking into account two Google search terms in order to identify credit demand: financiamento (type of loan used to finance goods) and empréstimo (a more general type of loan). Our framework is coupled with nonlinear features, such as Markov-switching and threshold point. We explore these nonlinearities to build identification strategies to disentangle the supply and demand forces which drive the credit market to equilibrium over time. We also show that the underlying nonlinearities significantly improves the performance of SS models on forecasting the household loans in Brazil, particularly in short-term horizons.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"499 - 527"},"PeriodicalIF":0.8,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48904926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract We undertake Monte Carlo simulation experiments to examine the effect of changing the frequency of observations and the data span on the Phillips, P. C. B., S. Shi, and J. Yu. 2015. “Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500.” International Economic Review 56 (4): 1043–78 generalised supremum ADF (GSADF) test for explosive behaviour via Monte Carlo simulations. We find that when a series is characterised by multiple bubbles (periodically collapsing), decreasing the frequency of observations is associated with profound power losses for the test. We illustrate the effects of temporal aggregation by examining two real house price data bases, namely the S&P Case–Shiller real house prices and the international real house price indices available at the Federal Reserve Bank of Dallas.
{"title":"Testing for exuberance in house prices using data sampled at different frequencies","authors":"Jesús Otero, Theodore Panagiotidis, Georgios Papapanagiotou","doi":"10.1515/snde-2021-0030","DOIUrl":"https://doi.org/10.1515/snde-2021-0030","url":null,"abstract":"Abstract We undertake Monte Carlo simulation experiments to examine the effect of changing the frequency of observations and the data span on the Phillips, P. C. B., S. Shi, and J. Yu. 2015. “Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500.” International Economic Review 56 (4): 1043–78 generalised supremum ADF (GSADF) test for explosive behaviour via Monte Carlo simulations. We find that when a series is characterised by multiple bubbles (periodically collapsing), decreasing the frequency of observations is associated with profound power losses for the test. We illustrate the effects of temporal aggregation by examining two real house price data bases, namely the S&P Case–Shiller real house prices and the international real house price indices available at the Federal Reserve Bank of Dallas.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"675 - 691"},"PeriodicalIF":0.8,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47934340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-26eCollection Date: 2022-09-01DOI: 10.1515/snde-2019-0084
Ba Chu
This paper introduces an unbiased estimator based on least squares involving time-specific cross-sectional averages for a first-order panel autoregression with a strictly exogenous covariate. The proposed estimator is straightforward to implement as long as the variables of interest have sufficient time variation. The number of cross-sections (N) and the number of time periods (T) can be large, and there is no restriction on the growth rate of N relative to T. It is demonstrated via both theory and a simulation study that the estimator is asymptotically unbiased, and it can provide correct empirical coverage probabilities for the 'true' coefficients of the model for various combinations of N and T. An empirical application is also provided to confirm the feasibility of the proposed approach.
{"title":"Time-specific average estimation of dynamic panel regressions.","authors":"Ba Chu","doi":"10.1515/snde-2019-0084","DOIUrl":"https://doi.org/10.1515/snde-2019-0084","url":null,"abstract":"<p><p>This paper introduces an unbiased estimator based on least squares involving time-specific cross-sectional averages for a first-order panel autoregression with a strictly exogenous covariate. The proposed estimator is straightforward to implement as long as the variables of interest have sufficient time variation. The number of cross-sections (<i>N</i>) and the number of time periods (<i>T</i>) can be large, and there is no restriction on the growth rate of <i>N</i> relative to <i>T</i>. It is demonstrated via both theory and a simulation study that the estimator is asymptotically unbiased, and it can provide correct empirical coverage probabilities for the 'true' coefficients of the model for various combinations of <i>N</i> and <i>T</i>. An empirical application is also provided to confirm the feasibility of the proposed approach.</p>","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 4","pages":"581-616"},"PeriodicalIF":0.8,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40457281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This paper analyzes the reaction function of monetary authority in India from 1997Q1 to 2019Q4 using nonlinear Taylor rule. It has been found that monetary policy reaction function (MPRF) in India is asymmetric and is influenced by the state of the economy, determined by the lagged interest rate. To capture such asymmetry, we have used a set of nonlinear models including smooth transition regression (STR) model, threshold regression (TR) model and Markov-switching regression (MSR) model along with the instrumental variable estimation technique. The analysis discloses that the behaviour of the Reserve Bank of India (RBI) is asymmetric, reacts aggressively to output gap in general and particularly during periods of high interest rate. Furthermore, the RBI reacts more to inflation and output gap during low volatile regimes in MSR models compared to high volatile regimes. We also found that there is a high degree of inertia in the policy rates of the RBI. The study concludes that nonlinear models may not only help in understanding the behaviour of the RBI but also prevent from making incorrect and misleading conclusions in Indian context.
{"title":"Asymmetries in the monetary policy reaction function: evidence from India","authors":"I. Shah, Srikanta Kundu","doi":"10.1515/snde-2019-0121","DOIUrl":"https://doi.org/10.1515/snde-2019-0121","url":null,"abstract":"Abstract This paper analyzes the reaction function of monetary authority in India from 1997Q1 to 2019Q4 using nonlinear Taylor rule. It has been found that monetary policy reaction function (MPRF) in India is asymmetric and is influenced by the state of the economy, determined by the lagged interest rate. To capture such asymmetry, we have used a set of nonlinear models including smooth transition regression (STR) model, threshold regression (TR) model and Markov-switching regression (MSR) model along with the instrumental variable estimation technique. The analysis discloses that the behaviour of the Reserve Bank of India (RBI) is asymmetric, reacts aggressively to output gap in general and particularly during periods of high interest rate. Furthermore, the RBI reacts more to inflation and output gap during low volatile regimes in MSR models compared to high volatile regimes. We also found that there is a high degree of inertia in the policy rates of the RBI. The study concludes that nonlinear models may not only help in understanding the behaviour of the RBI but also prevent from making incorrect and misleading conclusions in Indian context.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"541 - 558"},"PeriodicalIF":0.8,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44351767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This paper introduces rescaled variance [V/S] tests for seasonal stationarity. The V/S statistic is designed by Giraitis, L., P. Kokoszka, R. Leipus, and G. Teyssière. 2003. “Rescaled Variance and Related Tests for Long Memory in Volatility and Levels.” Journal of Econometrics 112: 265–94 to be the mean corrected versions of the KPSS statistic. In the seasonal context, Canova, F., and B. E. Hansen. 1995. “Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability.” Journal of Business & Economic Statistics 13: 237–52 present the seasonal generalization of the KPSS statistic. In this regard, I aim to strengthen the work of Canova, F., and B. E. Hansen. 1995. “Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability.” Journal of Business & Economic Statistics 13: 237–52 [CH] by mean correction in the seasonal framework. I obtain the asymptotic distributions of the seasonal V/S tests. The V/S tests enjoy better power performance than the CH tests while exhibiting similiar size performance. Furthermore, by data pre-filtering, I propose robustified versions of the V/S statistics to eliminate the unattended unit root problem observed in the CH tests.
{"title":"Rescaled variance tests for seasonal stationarity","authors":"K. C. Gogebakan","doi":"10.1515/snde-2021-0004","DOIUrl":"https://doi.org/10.1515/snde-2021-0004","url":null,"abstract":"Abstract This paper introduces rescaled variance [V/S] tests for seasonal stationarity. The V/S statistic is designed by Giraitis, L., P. Kokoszka, R. Leipus, and G. Teyssière. 2003. “Rescaled Variance and Related Tests for Long Memory in Volatility and Levels.” Journal of Econometrics 112: 265–94 to be the mean corrected versions of the KPSS statistic. In the seasonal context, Canova, F., and B. E. Hansen. 1995. “Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability.” Journal of Business & Economic Statistics 13: 237–52 present the seasonal generalization of the KPSS statistic. In this regard, I aim to strengthen the work of Canova, F., and B. E. Hansen. 1995. “Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability.” Journal of Business & Economic Statistics 13: 237–52 [CH] by mean correction in the seasonal framework. I obtain the asymptotic distributions of the seasonal V/S tests. The V/S tests enjoy better power performance than the CH tests while exhibiting similiar size performance. Furthermore, by data pre-filtering, I propose robustified versions of the V/S statistics to eliminate the unattended unit root problem observed in the CH tests.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"98 ","pages":"617 - 633"},"PeriodicalIF":0.8,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2021-0004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41282327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Unfortunately, time series problems do not appear in data singly. We focus on the joint occurrence of nonstationarity, seasonality and bounded data. Seasonal unit root tests and bounded unit root tests already exist in the literature, yet when all these issues are combined their performance needs improvement. That is why we offer a testing procedure for bounded seasonal unit root processes. The combination of these tests is not straightforward as the nonlinearity coming from bounds causes the limiting distribution of the proposed test statistic to be multivariate Brownian motion while the others have univariate distributions. The simulation exercises reveal that the existing tests, which ignores the presence of bounds or seasonality, suffer significant size problems. Our statistic removes the size distortions and also maintain satisfactory power performance.
{"title":"Regulated seasonal unit root process","authors":"B. Eroğlu, A. Pehlivan","doi":"10.1515/snde-2019-0110","DOIUrl":"https://doi.org/10.1515/snde-2019-0110","url":null,"abstract":"Abstract Unfortunately, time series problems do not appear in data singly. We focus on the joint occurrence of nonstationarity, seasonality and bounded data. Seasonal unit root tests and bounded unit root tests already exist in the literature, yet when all these issues are combined their performance needs improvement. That is why we offer a testing procedure for bounded seasonal unit root processes. The combination of these tests is not straightforward as the nonlinearity coming from bounds causes the limiting distribution of the proposed test statistic to be multivariate Brownian motion while the others have univariate distributions. The simulation exercises reveal that the existing tests, which ignores the presence of bounds or seasonality, suffer significant size problems. Our statistic removes the size distortions and also maintain satisfactory power performance.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"361 - 385"},"PeriodicalIF":0.8,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44275243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This study investigates the long-run and short-run relationship between consumption, income, financial and housing wealth, and a long-term interest rate for the 50 US states. Using an updated set of quarterly data from 1975 to 2018, we perform panel cointegration analysis allowing for cross-sectional dependence. We obtain the following results. First, there is strong evidence for cointegration among consumption and its determinants. Second, estimates of the housing wealth and financial wealth elasticity of consumption range from 0.072 to 0.115 and 0.044 to 0.080, respectively. Finally, Granger causality tests show that there is a bidirectional short-term causality between per capita consumption, income, and financial wealth in the short run and between all the variables in the long run.
{"title":"Consumption, personal income, financial wealth, housing wealth, and long-term interest rates: a panel cointegration approach for 50 US states","authors":"Dimitra Kontana, Stilianos Fountas","doi":"10.1515/snde-2020-0057","DOIUrl":"https://doi.org/10.1515/snde-2020-0057","url":null,"abstract":"Abstract This study investigates the long-run and short-run relationship between consumption, income, financial and housing wealth, and a long-term interest rate for the 50 US states. Using an updated set of quarterly data from 1975 to 2018, we perform panel cointegration analysis allowing for cross-sectional dependence. We obtain the following results. First, there is strong evidence for cointegration among consumption and its determinants. Second, estimates of the housing wealth and financial wealth elasticity of consumption range from 0.072 to 0.115 and 0.044 to 0.080, respectively. Finally, Granger causality tests show that there is a bidirectional short-term causality between per capita consumption, income, and financial wealth in the short run and between all the variables in the long run.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"417 - 435"},"PeriodicalIF":0.8,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48740371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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