Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.     

Are imports and remittances cointegrated for the Central and Eastern European countries?

In this article, we investigate the existence of long-run common trends between imports and remittances in 11 Central and Eastern European countries which are part of the European Union. Using the Engle–Granger two-step procedure, we determine that for all countries in our sample there are no long-run common trends (no cointegration) between imports and remittances. However, the results are mixed when running a Granger causality test. For nine countries, we can establish either a bidirectional or unidirectional Granger causality, indicating that past values of one variable have predictive content on the other variable. In two countries, there is no Granger causality between imports and remittances.     

COVID-19, stock market and sectoral contagion in US: a time-frequency analysis

We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.     

The government revenue and government expenditure nexus: empirical evidence from nine Asian countries

The nexus between government revenue and government expenditure has been an important topic in public economics. In this paper, we investigate evidence for cointegration and causality between government revenue and government expenditure for nine Asian countries. We use the recently developed bounds testing approach to cointegration and the conventional F-test to examine Granger causality. Our empirical results suggest that for three out of the nine countries government revenue and government expenditure are cointegrated. Our results on the direction of causation are mixed: (a) for Indonesia, Singapore, Sri Lanka in the short-run and for Nepal in both the short- and long-run we find support for the tax-and-spend hypothesis; (b) Indonesia and Sri Lanka are in conformity with the spend-and-tax hypothesis in the long-run; and (c) for other countries there is evidence of neutrality.     

客户信用评级体系的校准度检验研究

利用多种统计量对客户信用评级体系进行校准度检验,以对其准确性做出定量评估。同时,使用这些统计量对由两种不同方法构造的信用评级进行了实证对比检验,结果表明,校准度检验能够对客户信用评级的准确性做出有效评估。     

The Structural Relation Between Mortgage and Market Interest Rates

This paper analyzes the dynamic relationship between primary and secondary mortgage markets and the short-term and long-term market interest rates. Using a series of monthly data on fixed rate mortgage rates and GNMA rates, we explore the dependence and speed of adjustment in these primary and secondary mortgage rates to each other as well as to the long and short-term government rates. The results indicate that residential mortgage rates in general, appear to follow the long-term rate and are not very sensitive to movements in the short-term interest rate.     

Statistics for Studies of Human Welfare

Developments in the recent past have substantially increased our ability to measure, compute, and communicate. We take the view that a corresponding improved understanding of processes in the life sciences will come about only through more intensive studies of properties of statistical methods and algorithms and transparent, open source computing environments.     

中国和新加坡产业内贸易与规模经济关系的协整分析

中国和新加坡产业内贸易与规模经济存在着一种长期的均衡关系,新加坡生产企业的规模经济对产业内贸易的推动作用大于中国,中国和新加坡生产企业的规模经济与产业内贸易存在单向因果关系,即规模经济促进产业内贸易.     

油品测试用规格仪器国产化回眸

指出规格仪器是油品测试方法标准化的基础，总结了油品测试用规格仪器国产化的过程，并对今后的发展方向加以分析。