Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures

Using daily data from August 9, 2015, to July 7, 2020, this study examines the effects of economic policy uncertainty (EPU) on the returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. To this end, two new measures of EPU (Twitter-based economic uncertainty and Twitter-based market uncertainty) are considered. A Granger causality test using the recursive evolving window approach shows a significant causality between the Twitter-based EPU measures and the BTC/USD exchange rate from October 2016 to July 2017. Moreover, a significant causality was noted from the EPU measures to the ETH/USD exchange rate from June 2019 to February 2020 and from the EPU measures to the XRP/USD exchange rate from January 2020 to February 2020. The Twitter-based EPU measures primarily positively affect the returns of the related cryptocurrencies during these periods. These results are robust to different measures of Twitter-based EPU and different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.     

Net Equity and Debt Flows to Emerging Market and Developing Economies in the Post-Crisis Era

We investigate the determinants of net equity and debt flows into 60 emerging and developing countries during 1986–2012, with a special focus on the period following the onset of the global financial crisis (GFC). Our results controlling for endogeneity show that net equity flows to emerging markets were mostly influenced by global risk factors, while net debt flows were affected by country-specific factors. We further distinguish the factors that were more pronounced in determining net portfolio flows to emerging markets since the GFC. The US real interest rate had significant spillover effects on net equity flows after the GFC. An increase in country’s domestic credit attracted net debt inflows before the GFC, while it was associated with net equity outflows after the GFC. We also find that capital controls moderated net debt flows since the GFC.     

基于回弹法混凝土强度测定研究

介绍了回弹法测定混凝土强度的原理,利用最小二乘法求得了大庆地区混凝度强度测定的回弹法公式.     

土地利用现状评价与分析——基于权的最小平方法

根据沈阳市的特点,建立土地利用现状评价指标体系,利用权的最小平方法确定评价指标的权重。采用综合评价法从土地开发利用程度、土地集约利用程度、土地利用综合效益三方面对土地利用现状进行评价。结果表明:沈阳市土地开发利用程度、土地集约利用水平都远高于全省平均水平,土地利用综合效益略低于全省平均水平,土地利用综合效益有待提高。     

云南省城镇居民消费与收入关系的非参数回归分析

近二十多年来,非参数统计的方法已广泛应用于计量经济学的研究。由于不需要预先确定变量间的函数关系,对计量经济模型的估计和预测提供了多方面和灵活机动的表现形式。本文尝试将非参数估计理论引入到回归模型中,通过建立非参数回归模型及普通的线性回归模型对云南省城镇居民可支配收入及消费之间的关系进行比较研究。     

基于权的最小平方法的土地利用现状评价——以阜新市为例

研究目的：采用权的最小平方法对阜新市的土地利用现状进行评价。研究方法：文献资料法和实证分析法。研究结果：阜新市土地利用总体水平居辽宁省中等水平,评价结果与其他方法评价结果基本相符。研究结论：权的最小平方法在土地利用现状评价中应用是切实可行的。     

Consumer Preferences for Fresh Tomatoes in Benin using a Conjoint Analysis

Constraints related to the technical and socioeconomic aspects of adopting tomato varieties are well documented. However, preferences relating to the demand for this fruit are rarely studied. In fact, demand for the different varieties of tomatoes might be related to consumers’ preferences for the extrinsic (color, size) and intrinsic (taste, nutritive value, water content) characteristics specific to each variety. It is therefore indispensable to determine the characteristics of tomatoes preferred by consumers. We examine consumers’ preferences for tomato attributes among a sample of 600 consumers in four representative markets in the main cities in southern Benin. The study also identifies potential segments of consumers and the market shares of each profile for each segment. The study identifies four potential tomato market segments, two of which have a strong preference for local tomatoes, namely, those that can be conserved for long periods and those with a firm consistency.     

Transformations of the state variable and learning dynamics

This article examines dynamics in a model where agents forecast a one dimensional state variable through ordinary least squares regressions on the lagged values of the state variable. We study the stability properties of alternative transformations of the state variable, such as taking logarithms, which the agent can endogenously set forth. Surprisingly, for the considered class of economies, we found that the transformations that an econometrician would attempt are destabilizing, whereas alternative transformations, which an econometrician would never consider, such as convex transformations, are stabilizing. Therefore, we ironically find that in our set‐up, an active agent who is concerned about learning the economy’s dynamics and who in an attempt to improve forecasting transforms the state variable using standard transformations, is more likely to deviate from the steady state than a passive agent.     

Estimation employing a priori information within mass appraisal and hedonic pricing models

Both statistical appraisal and hedonic pricing models decompose houses into a set of individual characteristics. Regression estimates yield the contribution of each characteristic to total value. Unfortunately, straightforward application of OLS may produce untenable results such as implausible coefficient magnitudes or incorrect signs. Often the suspected cause is multicollinearity. This article examines the effect on estimation efficiency of differing levels of multicollinearity, R², and a priori information in the form of sub-market cost data, by comparing inequality restricted least squares (IRLS) with OLS in a series of Monte Carlo experiments. The IRLS procedure investigated here hybridizes the statistical market approach implemented by OLS, and the more traditional cost approach. The experiments show dramatic gains in estimation efficiency from exploiting a priori information through IRLS.     

Consistency of elementwise-weighted total least squares estimator in a multivariate errors-in-variables model <Emphasis Type="Bold">AX=B</Emphasis>

A multivariate measurement error model AXB is considered. The errors in [A,B] are rowwise independent, but within each row the errors may be correlated. Some of the columns are observed without errors, and in addition the error covariance matrices may differ from row to row. The total covariance structure of the errors is supposed to be known up to a scalar factor. The fully weighted total least squares estimator of X is studied, which in the case of normal errors coincides with the maximum likelihood estimator. We give mild conditions for weak and strong consistency of the estimator, when the number of rows in A increases. The results generalize the conditions of Gallo given for a univariate homoscedastic model (where B is a vector), and extend the conditions of Gleser given for the multivariate homoscedastic model. We derive the objective function for the estimator and propose an iteratively reweighted numerical procedure.Acknowledgements.A. Kukush is supported by a postdoctoral research fellowship of the Belgian office for Scientific, Technical and Cultural Affairs, promoting Scientific and Technical Collaboration with Central and Eastern Europe. S. Van Huffel is a full professor with the Katholieke Universiteit Leuven. This paper presents research results of the Belgian Programme on Interuniversity Poles of Attraction (IUAP Phase V-22), initiated by the Belgian State, Prime Ministers Office-Federal Office for Scientific, Technical and Cultural Affairs, of the Concerted Research Action (GOA) projects of the Flemish Government MEFISTO-666 (Mathematical Engineering for Information and Communication Systems Technology), of the IDO/99/03 project (K.U. Leuven) Predictive computer models for medical classification problems using patient data and expert knowledge, of the FWO projects G.0200.00, G.0078.01 and G.0270.02. The scientific responsibility is assumed by its authors. The authors would like to thank Maria Luisa Rastello and Amedeo Premoli for bringing the EW-TLS problem to their attention. The authors are grateful to two anonymous referees for the valuable comments.