Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed-frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across different models, extending the model specification by adding MA terms, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track using a specific form of intercept correction. Among these methods, adjusting the original nowcasts and forecasts by an amount similar to the nowcast and forecast errors made during the financial crisis and subsequent recovery seems to produce the best results for the US, notwithstanding the different source and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for 2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators become much more similar, all unfortunately indicating a much slower recovery than without adjustment, and very persistent negative effects on trend growth. Similar findings also emerge for forecasts by institutions, for survey forecasts, and for the other G7 countries.     

Forecast-error-based estimation of forecast uncertainty when the horizon is increased

Past forecast errors are employed frequently in the estimation of the unconditional forecast uncertainty, and several institutions have increased their forecast horizons in recent times. This work addresses the question of how forecast-error-based estimation can be performed if there are very few errors available for the new forecast horizons. It extends the results of Knüppel (2014) in order to relax the condition on the data structure that is required for the SUR estimator to be independent of unknown quantities. It turns out that the SUR estimator of the forecast uncertainty, which estimates the forecast uncertainty for all horizons jointly, tends to deliver large efficiency gains relative to the OLS estimator (i.e., the sample mean of the squared forecast errors for each individual horizon) in the case of increased forecast horizons. The SUR estimator is applied to the forecast errors of the Bank of England, the US Survey of Professional Forecasters, and the FOMC.     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

A Kaleckian Perspective on Financialisation and Distribution in Three Main Eurozone Countries before and after the Crisis: France,Germany and Spain

The purpose of this article is twofold. First, we examine if, and to what extent, a general Kaleckian analysis of the potential effects of financialisation on income shares in advanced capitalist economies is of relevance for the three Eurozone countries under investigation—France, Germany and Spain—in the period before the recent financial and economic crisis. Second, we study changes in the financialisation–distribution nexus that have occurred in the course of and after the financial and economic crisis. We find that the countries examined here have shown broad similarities regarding redistribution before the crisis, although there are some differences in the underlying determinants. These differences have continued during the period after the crisis and have led to different results in the development of distribution since then.     

农村集体经营性建设用地流转模式再审视：基于产权让渡与市场化的视角

研究目的:厘清集体经营性建设用地流转模式,推进集体建设用地入市改革。研究方法:以产权让渡及市场化为视角,采用矩阵分类法划分集体经营性建设用地流转模式,剖析不同流转模式特征与演进路径。研究结果:基于本研究视角可将集体经营性建设用地流转划分为6种模式,不同模式具有不同特征、运行条件、优缺点及收益分配格局,且其存在关联并遵循一定的演进规律。研究结论:规范市场下农地发展权及使用权流转模式将是当前改革的方向,需从法律法规上明确农地发展权相关规定;不同地区需因地制宜地选择流转模式及类型,探索具体实施办法,循序渐进推进流转改革与创新。     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.     

新型抛料分配式多点卸料输送机的研发与应用

通过对比几种常用的粮食入仓多点卸料设备所存在的问题,综合考虑绿色节能、密闭环保、可靠方便等方面,本文研制了一种新型抛料分配式多点卸料输送机,在国内多个项目中得到了很好的应用。     

What is the policy improvement of China’s land consolidation? Evidence from completed land consolidation projects in Shaanxi Province

Land consolidation plays an important role in increasing cultivated land, improving cultivated land quality and the ecological environment, and promoting the coordinated development of urban and rural areas. However, under the conditions of three decades of land consolidation being conducted and changing urban–rural human–land relationship, the areas of improvement in the land consolidation policy of China must be studied. This article analyzes the implementation and distribution characteristics of the land consolidation project completed in Shaanxi Province in 2018. Results show that land consolidation projects in Shaanxi are mainly land reclamation projects, cropland consolidation projects, and high-standard cropland consolidation projects. The increased cultivated land is mainly from land reclamation projects and cropland consolidation projects. The land consolidation projects in Aeolian Plateau Area, Loess Plateau Area, and Da Ba Mountain Area are mainly land reclamation projects. The land reclamation projects in Guan Zhong Plain Area and Qing Ling Mountain Area account for a large proportion. The spatial distribution of rural settlement consolidation projects, and rural settlement consolidation and land reclamation projects are mainly located in Guan Zhong Plain Area and distributed in the boundary area of Guan Zhong Plain Area and Loess Plateau Area. According to the characteristics of land consolidation projects and the changes of urban–rural human–land relationship, China should be prudent in or stop advancing land reclamation to increase cultivated land; cropland consolidation and high-standard cropland construction are vital ways to achieve China’s food security; and rural settlement consolidation should be carefully conducted in remote areas under the background of urbanization.