A nowcasting model for Ecuador: Implementing a time-varying mean output growth

We propose a model to nowcast the annual growth rate of real GDP for Ecuador, whose economy lacks timely macroeconomic information for some key variables and has gone through unstable periods due to its dependence on oil exports. Our specification combines monthly information for 30 macroeconomic and financial variables with quarterly information for real GDP in a mixed-frequency approach. Our setup includes a time-varying coefficient on the mean annual growth rate of output to allow the model to incorporate prolonged periods of low or high growth. The model produces more accurate nowcasts of real output growth in pseudo out-of-sample exercises than a nowcasting model that assumes a constant mean real GDP growth rate. We also conduct sensitivity analyses on our nowcasting model within the time-varying mean setup and find that including financial variables can be detrimental to the performance of the proposed model.     

Global uncertainties and portfolio flow dynamics of the BRICS countries

This paper investigates the dynamics of bond and stock market capital flows to BRICS countries under uncertainties such as global economic policy uncertainty and the US trade policy uncertainty. We use a time-varying Granger causality framework over the January 2008-November 2019 period to analyze the predictive power of uncertainties on capital flows in the form of bond and equity. The results show that the effects are heterogeneous across countries and stronger during the Global Financial Crisis period and post-2018 period while it lost its significance in the subsequent period. The negative influence of uncertainties on capital flows directed to BRICS countries is also evident in the results of non-parametric time-varying panel models. Overall, it is thought that the heterogeneous structure of the causality between uncertainty and portfolio flows into BRICS may present portfolio diversification benefits for global investors.     

EMPIRICAL ESTIMATION OF NON-LINEAR INPUT–OUTPUT MODELS: AN ENTROPY ECONOMETRICS APPROACH

Despite theoretical advances, non-linear input–output models have been empirically applied only to a limited extent. This is mainly due to the fact that the number of parameters to be estimated is much higher than the number of available data points. Taking advantage of the recent proliferation of input–output databases and by applying an estimation strategy that relies on entropy econometrics, this paper suggests a way to estimate the parameters that characterize non-linear relationships between inputs and output. This non-linear modelling allows for considering time-specific input coefficients, instead of fixed ones. Several types of multipliers can be derived from this non-linear model, and the proposed generalized maximum entropy (GME) estimator allows estimating them from time series or cross-sectional datasets of input–output tables. The proposed GME technique is illustrated by means of an empirical application that estimates the parameters that characterize a non-linear input–output model for the Spanish economy over the period 1995–2011.     

新疆旅游业投入产出分析

本文以新疆2002年和2007年投入产出表为依据,从直接消耗系数和完全消耗系数、感应度系数和影响力系数以及投入产出乘数效应这三方面对新疆旅游业进行投入产出分析后发现,新疆旅游业对新疆经济的推动作用有限,旅游业自身的发展依赖于交通运输业、批发零售业、住宿餐饮业及交通运输设备业的发展,且旅游业的发展并未带来交通运输业的显著发展。     

住宅用地基准地价的容积率系数修正新方法

容积率修正系数编制是土地评估领域探讨的热点之一。提出了先构建容积率、因素总分值与地价关系的地价模型,进而编制分级别的住宅用地容积率修正系数的新方法,并以北海市为例进行实证研究。研究表明:地理加权回归模型的拟合度明显优于最小二乘法,便于据此编制更精准的分级别容积率修正系数表;该方法引入因素总分值规避了传统区域修正方法的主观任意性问题,便于计算机进行批量快速处理,保证了编制的容积率修正系数的可靠性,在实践中行之有效。     

转移支付类型对省内县际间财力不均等的贡献——按收入来源进行的基尼系数分解

转移支付结构是影响财力均等化效应的重要因素之一,然而,对于一些特定类型转移支付的均等化效应,理论界和实践界都存在较大争议。文章运用基尼系数的收入来源分解法,对1999-2004年全国27个省、自治区的省内县际间财力差异进行分解,得到不同类型转移支付对财力不均等的贡献率。结果表明,因素法转移支付的均等化效果并不十分理想;转移支付类型对均等化效应的影响还存在一定的区域性差别,需要政策上的区别处理。     

Supply-side investments: An international analysis of the return and risk relationship in the Travel & Leisure sector

This study investigates supply-side investments in the tourism sector, analysing the return and risk relationship of investments in tourism across several countries. The performance of tourism sector companies listed on the stock exchange, for the top one dozen countries according to the World Economic Forum (WEF) tourism rankings, is investigated by region, across these countries and within each country by comparison to other sectors. Several metrics are used to compare the risk-adjusted returns, over a 15-year period ending March 2007 and sub-periods to check the persistence of performance over time. The results present a strikingly different ranking than those of the WEF. The implications for the flow of investment funds are of importance in a global capital market. Money will flow to those investments with the highest expected returns for a given risk level and this has consequential impacts for economic growth and employment in the tourism sector.     

INCOME DISTRIBUTIONS IN INPUT-OUTPUT MODELS

The analysis of income distribution (ID) has traditionally been of prime importance for economists and policy-makers. However, the standard input–output (I–O) model is not particularly well equipped for studying current issues such as the consequences of decreasing access to primary inputs or the effects of specific redistributive policies. This paper addresses this gap in the existing literature. We propose that IDs can excellently be studied by restructuring the I–O relations. A new coefficients matrix is defined, the so-called augmented input coefficients matrix. This matrix is the sum of the intermediate input coefficients matrix and newly constructed matrices of sector-specific input coefficients that represent the existing distribution of income. We show that shifts in the distribution can be modelled by attributing weights to these matrices and vary these according to system-specific rules. Numerical illustrations based on the existing literature are given throughout the paper.     

The Emergence of Second‐Tier Auditors in the US: Evidence from Investor Perceptions of Financial Reporting Credibility

We examine changes in the association between auditor type (Big 4, Second‐Tier, and Other non‐Big 4) and perceived financial reporting credibility in the wake of events (e.g., Andersen's failure, the implementation of SOX, creation of the PCAOB, etc.) which led to significant growth in Second‐Tier client portfolios and increased scrutiny of Second‐Tier audit practices. Our results reveal that financial reporting credibility of Second‐Tier clients was lower than that of Big 4 clients and was indistinguishable from that of Other non‐Big 4 clients pre‐Andersen. However, post‐Andersen, we find that financial reporting credibility of Second‐Tier clients is higher than that of Other non‐Big 4 clients and is indistinguishable from that of Big 4 clients. We expect that our results will be of interest to regulators, both in the United States and in the European Union, who have expressed concerns about the current state of competition in the audit market, management and boards of directors that are contemplating switching to a Second‐Tier audit firm, and academics investigating quality differences among audit firm types.     

Time-series–cross-section Data

This article treats the analysis of 'time-series–cross-section' (TSCS) data. Such data consists of repeated observations on a series of fixed units. Examples of such data are annual observations on the political economy of OECD nations in the post-war era. TSCS data is distinguished from 'panel' data, in that asymptotics are in the number of repeated observations, not the number of units.
The article begins by treating the complications of TSCS data in an 'old-fashioned' manner, that is, as a nuisance which causes estimation difficulties. It claims that TSCS data should be analyzed via ordinary least squares with 'panel correct standard errors' rather than generalized least squares methods. Dynamics should be modeled via a lagged dependent variable or, if appropriate, a single equation error correction model.
The article then treats more modern issues, in particular, the modeling of spatial effects and heterogeneity. It also claims that heterogeneity should be assessed with 'panel cross-validation' as well as more standard tests. The article concludes with a discussion of estimation in the presence of a binary dependent variable.