Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

Pre-announcement and timing: The effects of a government expenditure shock

An econometric strategy to identify a pre-announced fiscal policy shock is proposed. I show that the reduced form innovations can be recovered by estimating a Vector-moving-average model using the Kalman filter. The structural effects are identified exploiting the shock's pre-announced nature, which leads to potentially different signs of the responses of some endogenous variables during the announcement and after the realization of the shock. I illustrate my strategy by identifying a pre-announced shock to government consumption expenditures. I find that the response of private consumption is significantly negative on impact, rises and becomes significantly positive two quarters after the realization of the policy shock.     

Nowcasting causality in mixed frequency vector autoregressive models

This paper introduces nowcasting causality as the mixed-frequency version of instantaneous causality. We analyze the relationship between nowcasting and Granger causality in a mixed-frequency VAR and illustrate its impact on the significance of high-frequency variables in mixed-frequency conditional models.     

House prices,credit and the effect of monetary policy in Norway: evidence from structural VAR models

This paper investigates the responses of house prices and household credit to monetary policy shocks in Norway, using Bayesian structural VAR models. The analysis indicates that the effect of a monetary policy shock on house prices is large, while the effect on household credit is muted. This is consistent with a relatively small refinancing rate (refinancing rate refers to the share of outstanding mortgages that are refinanced each period due to changes in, for example, house prices or interest rate) of the mortgage stock each quarter. Using monetary policy to guard against financial instability by mitigating property-price movements may prove effective, but trying to mitigate household credit may prove costly in terms of GDP and inflation variation.     

The franc shock and Swiss GDP: how long does it take to start feeling the pain?

The article addresses the question on what is the typical time horizon over which a full transmission of movements in the real exchange rate takes place into real economy. We base our analysis on the mixed-frequency small-scale dynamic factor model (DFM) proposed by Siliverstovs in 2012 fitted to the Swiss data. In this article, we augment the benchmark model with the real exchange rate of the Swiss franc vis-a-vis currencies of its 24 trading partners, while keeping the rest of model specification intact. We are interested in investigating the relationship between the common latent factor, representing the Swiss business cycle, and the real exchange rate. We explore the temporal relationship between these two variables by varying the time lag with which the real exchange rate enters the factor model by recording the magnitude and statistical significance of the factor loading coefficient in the equation pertaining to the real exchange rate variable. Our main conclusion is that the fluctuations in the exchange rate start influencing real economy after 1 month and their effect is practically over after 13 months. The largest effect is recorded at the time horizon of about 6 to 9 months.     

Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions

We study the transmission of monetary policy to macroeconomic variables with structural time-varying coefficient vector autoregressions in the Czech Republic, Hungary and Poland, in comparison with that in the euro area. These three countries have experienced changes in monetary policy regimes and went through substantial structural changes, which call for the use of a time-varying parameter analysis. Our results indicate that the impact on output of a monetary shock changed over time. At the point of the last observation of our sample, the fourth quarter of 2011, among the three countries, monetary policy was most powerful in Poland and not much less strong than the transmission in the euro area. We discuss various factors that can contribute to differences in monetary transmission, such as financial structure, labour market rigidities, industry composition, exchange rate regime, credibility of monetary policy and trade openness.     

中国货币需求均衡水平调节的实证研究

通过构建以收入、股票市场市值、利率、预期通货膨胀率以及汇率为自变量的货币需求计量模型,本文运用协整检验、误差修正模型和脉冲响应函数,以我国1994年第一季度至2009年第二季度的季度数据为样本,对我国货币需求的均衡水平调节状态进行了实证研究。研究表明,以上变量与实际货币需求存在长期稳定的均衡关系,货币需求在短期内存在向长期均衡水平调整的自发调节机制,各自变量对货币需求的影响程度各异且具有不同的动态过程。最后,根据实证结果提出了一些政策建议。     

Macro-uncertainty and financial stress spillovers in the Eurozone

This paper studies macro-uncertainty and financial distress spillovers within the Eurozone. We propose a novel methodology to derive the indices of spillovers, by using a Global Vector autoregressive model fitted to data sampled at mixed-frequencies. We find that macro-uncertainty and financial stress are relatively disconnected in the Eurozone. We also show that connectedness between core and periphery Eurozone countries mainly operates through financial stress and it decreases since the outbreak of the Eurozone sovereign debt crisis (with an increasing role played by peripheral countries). As a result, investors and policymakers should monitor separately macro-uncertainty and financial stress. Finally, we find that the mixed-frequency data should be taken into account in this context, otherwise, the spillovers can be underestimated.     

汇率波动、货币政策传导渠道及有效性——兼论"不可能三角"在我国的适用性

本文尝试把人民币汇率波动纳入货币政策中介目标监控体系,采用1996年1季度至2008年2季度的季度数据进行实证检验。研究表明:(1)我国货币政策是通过货币渠道来影响实际经济总量的,并且狭义货币供应量更能实现对实际产出目标的传导和调控;(2)人民币汇率波动的扩大会减少货币供应量;(3)不可能三角在我国是成立的;(4)将人民币汇率波动纳入货币政策中介目标监控体系能提高货币政策的有效性。     

Fiscal multipliers in a structural VEC model with mixed normal errors

This paper estimates the effects of fiscal policy shocks on GDP in the United States with a vector error correction (VEC) model in which shocks are identified by exploiting the non-normal distribution of the model residuals. Unlike previous research, the model used here takes into account cointegation between the variables, and applies a data driven method to identify fiscal policy shocks. The approach also allows statistical testing of previous identification strategies, which may help discriminate between them and hence also explain differences between various fiscal multiplier estimates. Our results show that a deficit financed government spending shock has a weak negative effect on output, whereas a tax increase to finance government spending has a positive impact on GDP.     

Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)

Governments, central banks, private firms and others need high frequency information on the state of the economy for their decision making. However, a key indicator like GDP is only available quarterly and that too with a lag. Hence decision makers use high frequency daily, weekly or monthly information to project GDP growth in a given quarter. This method, known as nowcasting, started out in advanced country central banks using bridge models. Nowcasting is now based on more advanced techniques, mostly dynamic factor models. In this paper we use a novel approach, a Factor Augmented Time Varying Coefficient Regression (FA-TVCR) model, which allows us to extract information from a large number of high frequency indicators and at the same time inherently addresses the issue of frequent structural breaks encountered in Indian GDP growth. One specification of the FA-TVCR model is estimated using 19 variables available for a long period starting in 2007–08:Q1. Another specification estimates the model using a larger set of 28 indicators available for a shorter period starting in 2015–16:Q1. Comparing our model with two alternative models, we find that the FA-TVCR model outperforms a Dynamic Factor Model (DFM) model and a univariate Autoregressive Integrated Moving Average (ARIMA) model in terms of both in-sample and out-of-sample Root Mean Square Error (RMSE). Further, comparing the predictive power of the three models using the Diebold-Mariano test, we find that FA-TVCR model outperforms DFM consistently. In terms of out-of-sample forecast accuracy both the FA-TVCR model and the ARIMA model have the same predictive accuracy under normal conditions. However, the FA-TVCR model outperforms the ARIMA model when applied for nowcasting in periods of major shocks like the Covid–19 shock of 2020–21.

     

基金业绩溢出效应及对开放式基金家族造星行为的影响*

本文以2011年第一季度至2015年第四季度我国所有股票型开放式基金为样本,通过引入虚拟变量,分别从基金家族层面构建了基金家族特征与家族资金净流入、单个基金特征与单个基金资金净流入之间的关系模型,重点考察了明星（垃圾）基金的存在对家族净资金流入的影响。研究发现“明星基金”对整个基金家族存在溢出效应,而“垃圾基金”则并没有发生反向溢出。基于这种非对称性特点,进一步使用面板数据logit模型研究了溢出效应对基金家族造星行为的影响,并提出造星主体的识别特征,即前期无明星基金、基金间超额收益标准差较高且规模较大的家族,下一期出现明星基金的概率大大提高。     

Towards an Understanding of Some Business Cycle Characteristics

For many years economists have debated the 'causes' of business cycles. Very little of this analysis has been closely matched with business cycle characteristics as measured by NBER-type dating methods. After summarising data on business cycle characteristics for a wide variety of countries, the article shows that an extremely simple statistical model of output growth, viz. that it is uncorrelated from month to month or quarter to quarter, produces business cycles that are close to those seen in practice. The demonstration involves the analysis of data simulated from this simple statistical model as well as some analytical work using a standard definition of a recession as being two quarters of negative growth. As well as explaining the average length of a cycle this model also accounts for the asymmetry between the lengths of expansions and contractions through the relative magnitudes of the trend rate of growth of the economy and the standard deviation of the shocks that impinge upon it.     

Does monetary policy affect the long-run expectations of non-stationary real interest rates?

In this article, we analyse whether the monetary policy affects the long-run expectation of the non-stationary real interest rate. The analysis is conducted through Beveridge–Nelson trend decomposition within a cointegrated vector autoregressive model based on the New Keynesian framework. We suggest an augmented test of the conventional co-integration test on the non-stationarity of the real interest rate, which checks whether the co-integration coefficient of inflation is one and the output gap affects the co-integration equilibrium of the nominal interest rate. We further suggest decomposing the long-run expectation of the non-stationary real interest rate into three trends: the interest rate shock (including the monetary shock), inflation shock and output gap shock. According to empirical analyses using monthly US data after the Korean War, the long-run expectation of the non-stationary real interest rate contains an interest rate shock trend and the impulse of the federal fund target rate induces a significant response of the interest rate shock trend. However, the interest rate shock trend has a very small portion of the long-run expectation of the non-stationary real interest rate, which may explain why the monetary policy was not particularly effective in the economic recovery after the global financial crisis.     

The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey

This paper introduces a new nowcasting model of the French quarterly real GDP growth rate (MIBA), developed at the Banque de France and based on monthly business surveys. The model is designed to target initial announcements of GDP in a mixed-frequency framework. The selected equations for each forecast horizon are consistent with the time frame of real-time nowcasting exercises: the first one includes mainly information on the expected evolution of economic activity, while the second and third equations rely more on information on observed business outcomes. The predictive accuracy of the model increases over the forecast horizon, consistent with the gradual increase in available information. Furthermore, the model outperforms a wide set of alternatives, such as its previous version and MIDAS regressions, although not a specification including also hard data. Further research should evaluate the performance of the MIBA model with respect to promising alternative approaches for nowcasting GDP (e.g. mixed-frequency factor models with targeted predictors), and consider forecast combinations and density forecasts.     

DOES NEOCLASSICAL THEORY ACCOUNT FOR THE EFFECTS OF BIG FISCAL SHOCKS? EVIDENCE FROM WORLD WAR II*

Much debate surrounds the usefulness of the neoclassical growth model for assessing the macroeconomic impact of fiscal shocks. We test the theory using data from World War II, which is by far the largest fiscal shock in the history of the United States. We take observed changes in fiscal policy during the war as inputs into a parameterized, dynamic general equilibrium model and compare the values of all variables in the model to the actual values of these variables in the data. Our main finding is that the theory quantitatively accounts for macroeconomic activity during this big fiscal shock.     

Measuring Monetary Policy in Germany: A Structural Vector Error Correction Approach

Abstract. A structural vector error correction (SVEC) model is used to investigate several monetary policy issues. While being data-oriented the SVEC framework allows structural modeling of the short-run and long-run properties of the data. The statistical model is estimated with monthly German data for 1975–98 where a structural break is detected in 1984. After splitting the sample, three stable long-run relations are found in each subsample which can be interpreted in terms of a money-demand equation, a policy rule and a relation for real output, respectively. Since the cointegration restrictions imply a particular shape of the long-run covariance matrix this information can be used to distinguish between permanent and transitory innovations in the estimated system. Additional restrictions are introduced to identify a monetary policy shock.     

Is the exchange rate a shock absorber or a source of shocks? Evidence from the U.S.

We examine the stabilization role of the exchange rate in the U.S. economy using a factor augmented vector autoregression model. We find that exchange rate shock explains a large fraction of the variation in exchange rate and transmits major disturbances to the real economy. Further, we find that demand and supply shocks explain less than a quarter of the exchange rate movement. We provide robust evidence that although the exchange rate plays some role as a shock absorber, its role as an independent source of shocks is more dominant for the U.S. economy. The foreign exchange market breeds its own shocks which are destabilizing not only to the value of the dollar but to the overall economy as well. Our results suggest that policymakers need to take foreign exchange market fluctuations into account when making macroeconomic policy decisions.     

The Great Collapse in Value Added Trade

This paper studies the great collapse in value added trade using a structural decomposition analysis. We show that changes in vertical specialization accounted for more than 40% of the great trade collapse. Second, we find that the drop in the overall level of demand accounted for roughly a quarter of the decline in value added exports while just under one third was due to compositional changes in final demand. Finally, we demonstrate that the dichotomy between services and manufacturing sectors observed in gross exports during the great trade collapse is not apparent in value added trade data.