Abstract This paper presents a Bayesian sampling approach to bandwidth estimation for the local linear estimator of the regression function in a nonparametric regression model. In the Bayesian sampling approach, the error density is approximated by a location-mixture density of Gaussian densities with means the individual errors and variance a constant parameter. This mixture density has the form of a kernel density estimator of errors and is referred to as the kernel-form error density (c.f. Zhang, X., M. L. King, and H. L. Shang. 2014. “A Sampling Algorithm for Bandwidth Estimation in a Nonparametric Regression Model with a Flexible Error Density.” Computational Statistics & Data Analysis 78: 218–34.). While (Zhang, X., M. L. King, and H. L. Shang. 2014. “A Sampling Algorithm for Bandwidth Estimation in a Nonparametric Regression Model with a Flexible Error Density.” Computational Statistics & Data Analysis 78: 218–34) use the local constant (also known as the Nadaraya-Watson) estimator to estimate the regression function, we extend this to the local linear estimator, which produces more accurate estimation. The proposed investigation is motivated by the lack of data-driven methods for simultaneously choosing bandwidths in the local linear estimator of the regression function and kernel-form error density. Treating bandwidths as parameters, we derive an approximate (pseudo) likelihood and a posterior. A simulation study shows that the proposed bandwidth estimation outperforms the rule-of-thumb and cross-validation methods under the criterion of integrated squared errors. The proposed bandwidth estimation method is validated through a nonparametric regression model involving firm ownership concentration, and a model involving state-price density estimation.
{"title":"Bayesian bandwidth estimation for local linear fitting in nonparametric regression models","authors":"H. Shang, Xibin Zhang","doi":"10.1515/snde-2018-0050","DOIUrl":"https://doi.org/10.1515/snde-2018-0050","url":null,"abstract":"Abstract This paper presents a Bayesian sampling approach to bandwidth estimation for the local linear estimator of the regression function in a nonparametric regression model. In the Bayesian sampling approach, the error density is approximated by a location-mixture density of Gaussian densities with means the individual errors and variance a constant parameter. This mixture density has the form of a kernel density estimator of errors and is referred to as the kernel-form error density (c.f. Zhang, X., M. L. King, and H. L. Shang. 2014. “A Sampling Algorithm for Bandwidth Estimation in a Nonparametric Regression Model with a Flexible Error Density.” Computational Statistics & Data Analysis 78: 218–34.). While (Zhang, X., M. L. King, and H. L. Shang. 2014. “A Sampling Algorithm for Bandwidth Estimation in a Nonparametric Regression Model with a Flexible Error Density.” Computational Statistics & Data Analysis 78: 218–34) use the local constant (also known as the Nadaraya-Watson) estimator to estimate the regression function, we extend this to the local linear estimator, which produces more accurate estimation. The proposed investigation is motivated by the lack of data-driven methods for simultaneously choosing bandwidths in the local linear estimator of the regression function and kernel-form error density. Treating bandwidths as parameters, we derive an approximate (pseudo) likelihood and a posterior. A simulation study shows that the proposed bandwidth estimation outperforms the rule-of-thumb and cross-validation methods under the criterion of integrated squared errors. The proposed bandwidth estimation method is validated through a nonparametric regression model involving firm ownership concentration, and a model involving state-price density estimation.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"55 - 71"},"PeriodicalIF":0.8,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2018-0050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45183100","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 proposes parametric two-step procedures for assessing the stability of cross-sectional dependency measures in the presence of potential breaks in the marginal distributions. The procedures are based on formerly proposed sup-LR tests in which restricted and unrestricted likelihood functions are compared with each other. First, we show theoretically that standard asymptotics do not hold in this situation. We propose a suitable bootstrap scheme and derive test statistics in different commonly used settings. The properties of the test statistics and precision of the associated change-point estimator are analysed and compared with existing non-parametric methods in various Monte Carlo simulations. These studies reveal advantages in test power for higher-dimensional data and an almost uniform superiority of the sup-LR test in terms of precision of the change-point estimator. We then apply this method to equity returns of European banks during the financial crisis of 2008.
{"title":"Testing constant cross-sectional dependence with time-varying marginal distributions in parametric models","authors":"Matthias Kaldorf, Dominik Wied","doi":"10.1515/snde-2019-0043","DOIUrl":"https://doi.org/10.1515/snde-2019-0043","url":null,"abstract":"Abstract This paper proposes parametric two-step procedures for assessing the stability of cross-sectional dependency measures in the presence of potential breaks in the marginal distributions. The procedures are based on formerly proposed sup-LR tests in which restricted and unrestricted likelihood functions are compared with each other. First, we show theoretically that standard asymptotics do not hold in this situation. We propose a suitable bootstrap scheme and derive test statistics in different commonly used settings. The properties of the test statistics and precision of the associated change-point estimator are analysed and compared with existing non-parametric methods in various Monte Carlo simulations. These studies reveal advantages in test power for higher-dimensional data and an almost uniform superiority of the sup-LR test in terms of precision of the change-point estimator. We then apply this method to equity returns of European banks during the financial crisis of 2008.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"1 - 24"},"PeriodicalIF":0.8,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49652123","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 is about identifying structural shocks in noisy-news models using structural vector autoregressive moving average (SVARMA) models. We develop a new identification scheme and efficient Bayesian methods for estimating the resulting SVARMA. We discuss how our identification scheme differs from the one which is used in existing theoretical and empirical models. Our main contributions lie in the development of methods for choosing between identification schemes. We estimate specifications with up to 20 variables using US macroeconomic data. We find that our identification scheme is preferred by the data, particularly as the size of the system is increased and that noise shocks generally play a negligible role. However, small models may overstate the importance of noise shocks.
{"title":"Choosing between identification schemes in noisy-news models","authors":"J. Chan, Eric Eisenstat, G. Koop","doi":"10.1515/SNDE-2020-0016","DOIUrl":"https://doi.org/10.1515/SNDE-2020-0016","url":null,"abstract":"Abstract This paper is about identifying structural shocks in noisy-news models using structural vector autoregressive moving average (SVARMA) models. We develop a new identification scheme and efficient Bayesian methods for estimating the resulting SVARMA. We discuss how our identification scheme differs from the one which is used in existing theoretical and empirical models. Our main contributions lie in the development of methods for choosing between identification schemes. We estimate specifications with up to 20 variables using US macroeconomic data. We find that our identification scheme is preferred by the data, particularly as the size of the system is increased and that noise shocks generally play a negligible role. However, small models may overstate the importance of noise shocks.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"26 1","pages":"99 - 136"},"PeriodicalIF":0.8,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/SNDE-2020-0016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46177042","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}
H. Boubaker, G. Canarella, Rangan Gupta, S. Miller
Abstract We report the results of applying several long-memory models to the historical monthly U.S. inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We find that the time-varying approach to estimating inflation persistence outperforms the models that assume a constant long-memory process. In addition, we examine the link between inflation persistence and exchange rate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflation persistence. This finding, however, is less pronounced during the era of the Great Moderation and the Federal Reserve System’s commitment to inflation targeting.
{"title":"Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation","authors":"H. Boubaker, G. Canarella, Rangan Gupta, S. Miller","doi":"10.1515/SNDE-2018-0116","DOIUrl":"https://doi.org/10.1515/SNDE-2018-0116","url":null,"abstract":"Abstract We report the results of applying several long-memory models to the historical monthly U.S. inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We find that the time-varying approach to estimating inflation persistence outperforms the models that assume a constant long-memory process. In addition, we examine the link between inflation persistence and exchange rate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflation persistence. This finding, however, is less pronounced during the era of the Great Moderation and the Federal Reserve System’s commitment to inflation targeting.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"289 - 310"},"PeriodicalIF":0.8,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/SNDE-2018-0116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44181502","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 extends the buffered autoregressive model to the buffered vector error-correction model (VECM). Least squares estimation and a reduced-rank estimation are discussed, and the consistency of the estimators on the delay parameter and threshold parameters is derived. We also propose a supWald test for the presence of buffer-type threshold effect. Under the null hypothesis of no threshold, the supWald test statistic converges to a function of Gaussian process. A bootstrap method is proposed to obtain the p-value for the supWald test. We investigate the effectiveness of our methods by simulation studies. We apply our model to study the monthly Federal bond rates of United States. We find the evidences of buffering regimes and the asymmetric error-correction effect.
{"title":"Buffered vector error-correction models: an application to the U.S. Treasury bond rates","authors":"Renjie Lu, P. Yu","doi":"10.1515/snde-2019-0047","DOIUrl":"https://doi.org/10.1515/snde-2019-0047","url":null,"abstract":"Abstract This paper extends the buffered autoregressive model to the buffered vector error-correction model (VECM). Least squares estimation and a reduced-rank estimation are discussed, and the consistency of the estimators on the delay parameter and threshold parameters is derived. We also propose a supWald test for the presence of buffer-type threshold effect. Under the null hypothesis of no threshold, the supWald test statistic converges to a function of Gaussian process. A bootstrap method is proposed to obtain the p-value for the supWald test. We investigate the effectiveness of our methods by simulation studies. We apply our model to study the monthly Federal bond rates of United States. We find the evidences of buffering regimes and the asymmetric error-correction effect.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"267 - 287"},"PeriodicalIF":0.8,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44722129","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 propose a new volatility process in which parameters vary over time according to an artificial neural network (ANN). We prove the process’s stationarity as well as the global identification of the parameters. Since ANNs require economic series as input variables, we develop a shrinkage approach to select which explanatory variables are relevant to forecast volatility. Empirically, the proposed model favorably compares with other flexible processes in terms of in-sample fit on six financial returns. It also delivers accurate short-term volatility predictions in terms of root mean squared errors and the predictive likelihood criterion. For long-term forecasts, it can be competitive with the Markov-switching generalized autoregressive conditional heteroskedastic (MS-GARCH) model if appropriate exogenous variables are used. Since our new type of time-varying parameter (TVP) process is based on a universal approximator, the approach can readily revisit and potentially improve many standard TVP applications.
{"title":"Modeling time-varying parameters using artificial neural networks: a GARCH illustration","authors":"M. N. Donfack, A. Dufays","doi":"10.1515/snde-2019-0091","DOIUrl":"https://doi.org/10.1515/snde-2019-0091","url":null,"abstract":"Abstract We propose a new volatility process in which parameters vary over time according to an artificial neural network (ANN). We prove the process’s stationarity as well as the global identification of the parameters. Since ANNs require economic series as input variables, we develop a shrinkage approach to select which explanatory variables are relevant to forecast volatility. Empirically, the proposed model favorably compares with other flexible processes in terms of in-sample fit on six financial returns. It also delivers accurate short-term volatility predictions in terms of root mean squared errors and the predictive likelihood criterion. For long-term forecasts, it can be competitive with the Markov-switching generalized autoregressive conditional heteroskedastic (MS-GARCH) model if appropriate exogenous variables are used. Since our new type of time-varying parameter (TVP) process is based on a universal approximator, the approach can readily revisit and potentially improve many standard TVP applications.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"311 - 343"},"PeriodicalIF":0.8,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43851702","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 propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial time series, and is an alternative to approximate maximum likelihood methods. We illustrate our analysis using hyperinflation episodes of Latin American countries.
{"title":"Selecting between causal and noncausal models with quantile autoregressions","authors":"Alain Hecq, Li Sun","doi":"10.1515/SNDE-2019-0044","DOIUrl":"https://doi.org/10.1515/SNDE-2019-0044","url":null,"abstract":"Abstract We propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial time series, and is an alternative to approximate maximum likelihood methods. We illustrate our analysis using hyperinflation episodes of Latin American countries.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"393 - 416"},"PeriodicalIF":0.8,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/SNDE-2019-0044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67095710","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}
Keiichi Goshima, H. Ishijima, M. Shintani, Hiroki Yamamoto
Abstract We construct business cycle indexes based on the daily Japanese newspaper articles and estimate the Phillips curve model to forecast inflation at a daily frequency. We find that the news-based leading indicator, constructed from the topic on future economic conditions, is useful in forecasting the inflation rate in Japan.
{"title":"Forecasting Japanese inflation with a news-based leading indicator of economic activities","authors":"Keiichi Goshima, H. Ishijima, M. Shintani, Hiroki Yamamoto","doi":"10.1515/SNDE-2019-0117","DOIUrl":"https://doi.org/10.1515/SNDE-2019-0117","url":null,"abstract":"Abstract We construct business cycle indexes based on the daily Japanese newspaper articles and estimate the Phillips curve model to forecast inflation at a daily frequency. We find that the news-based leading indicator, constructed from the topic on future economic conditions, is useful in forecasting the inflation rate in Japan.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"111 - 133"},"PeriodicalIF":0.8,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/SNDE-2019-0117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47457960","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 study the effect of factor substitutability in the neoclassical growth model with variable elasticity of substitution. We consider two otherwise identical economies differing uniquely in their initial factor substitutability with Variable-Elasticity-of-Substitution (VES), Sobelow or Sigmoidal technologies. If the initial capital per capita is below its steady-state value, the economy with the higher initial elasticity of substitution will feature a higher steady-state income and capital per capita irrespective of whether the production technology is VES, Sobelow or Sigmoidal. Numerical results are provided to compare the effect of a higher elasticity of substitution in the Constant-Elasticity-of-Substitution (CES) model versus the models with variable-elasticity-of-substitution technology.
{"title":"Variable elasticity of substitution and economic growth in the neoclassical model","authors":"Manuel A. Gómez","doi":"10.1515/SNDE-2019-0145","DOIUrl":"https://doi.org/10.1515/SNDE-2019-0145","url":null,"abstract":"Abstract We study the effect of factor substitutability in the neoclassical growth model with variable elasticity of substitution. We consider two otherwise identical economies differing uniquely in their initial factor substitutability with Variable-Elasticity-of-Substitution (VES), Sobelow or Sigmoidal technologies. If the initial capital per capita is below its steady-state value, the economy with the higher initial elasticity of substitution will feature a higher steady-state income and capital per capita irrespective of whether the production technology is VES, Sobelow or Sigmoidal. Numerical results are provided to compare the effect of a higher elasticity of substitution in the Constant-Elasticity-of-Substitution (CES) model versus the models with variable-elasticity-of-substitution technology.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":"25 1","pages":"345 - 364"},"PeriodicalIF":0.8,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/SNDE-2019-0145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43248383","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}
T. Faulwasser, M. Gross, W. Semmler, Prakash Loungani
Abstract After the financial market meltdown and the Great Recession of the years 2007–9, the financial market-macro link has become an important issue in monetary policy modeling. We develop a dynamic model that contains a nonlinear Phillips curve, a dynamic output equation, and a nonlinear credit flow equation – capturing the importance of credit cycles, risk premia, and credit spreads. Our Nonlinear Quadratic Model (NLQ) model has three dynamic state equations and a quadratic objective function. It can be used to evaluate the response of central banks to the Great Recession in moving from conventional to unconventional monetary policy. We solve the model with a new numerical procedure using estimated parameters for the euro area. We conduct simulations to explore the (de)stabilizing effects of the nonlinearities in the model. We demonstrate that credit flows, risk premia, and credit spreads play an important role as an amplification mechanism and in affecting the transmission of monetary policy. We thereby highlight the importance of the natural rate of interest as an anchor for a central bank target and the weight it places on the credit flows for the effectiveness of unconventional monetary policy. Our model is similar in structure compared to larger scale macro-econometric models which many central banks employ.
{"title":"Unconventional monetary policy in a nonlinear quadratic model","authors":"T. Faulwasser, M. Gross, W. Semmler, Prakash Loungani","doi":"10.1515/snde-2019-0099","DOIUrl":"https://doi.org/10.1515/snde-2019-0099","url":null,"abstract":"Abstract After the financial market meltdown and the Great Recession of the years 2007–9, the financial market-macro link has become an important issue in monetary policy modeling. We develop a dynamic model that contains a nonlinear Phillips curve, a dynamic output equation, and a nonlinear credit flow equation – capturing the importance of credit cycles, risk premia, and credit spreads. Our Nonlinear Quadratic Model (NLQ) model has three dynamic state equations and a quadratic objective function. It can be used to evaluate the response of central banks to the Great Recession in moving from conventional to unconventional monetary policy. We solve the model with a new numerical procedure using estimated parameters for the euro area. We conduct simulations to explore the (de)stabilizing effects of the nonlinearities in the model. We demonstrate that credit flows, risk premia, and credit spreads play an important role as an amplification mechanism and in affecting the transmission of monetary policy. We thereby highlight the importance of the natural rate of interest as an anchor for a central bank target and the weight it places on the credit flows for the effectiveness of unconventional monetary policy. Our model is similar in structure compared to larger scale macro-econometric models which many central banks employ.","PeriodicalId":46709,"journal":{"name":"Studies in Nonlinear Dynamics and Econometrics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/snde-2019-0099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45034223","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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