IMPROVING HUMAN DEVELOPMENT: A LONG‐RUN VIEW

Abstract The pessimistic flavour of the Human Development Reports appears to be in contradiction with their own numbers as developing countries fare comparatively better in human development than in per capita GDP terms. This paper attempts to bridge this gap by providing a new, ‘improved’ human development index (IHDI), informed by welfare economics. The IHDI is presented here alongside the United Nations Development Programme's (UNDP) HDI for the world and its main regions since the late 19th century. Social dimensions in the IHDI are derived, following Kakwani (Journal of Development Economics 41 (1993), pp. 307–336), with a convex achievement function, whereas a geometric average is employed to combine its dimensions (longevity, knowledge and income). Thus, the IHDI does not conceal the gap between rich and poor countries and casts a much less optimistic view than the conventional UNDP index, while it fits with the UNDP concern for international differences. The paper's findings highlight main weaknesses in human development dimensions of present‐day developing countries.     

Forecasting GDP growth with NIPA aggregates: In search of core GDP

In addition to GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide a variety of measures of economic activity, including gross domestic income and other aggregates that exclude one or more of the components that make up GDP. Similarly to the way in which economists have attempted to use core inflation—which excludes volatile energy and food prices—to predict headline inflation, the omission of GDP components may be useful in extracting a signal as to where GDP is going. We investigate the extent to which these NIPA aggregates constitute “core GDP.” In an out-of-sample forecasting exercise using a novel real-time dataset of NIPA aggregates, we find that consumption growth and the growth of GDP excluding inventories and trade have historically outperformed a canonical univariate benchmark for forecasting GDP growth, suggesting that these are promising measures of core GDP growth.     

An Implicit Törnqvist Index of Real GDP

Recently much attention has been devoted to superlative indexes in the context of the national accounts. In this paper we advocate the use of the implicit Törnqvist quantity index to measure real GDP. This index, which has been proposed by Diewert and Morrison (1986), has never received serious consideration in the literature. Yet, compared to the better-known Fisher index, the implicit Törnqvist index of real GDP has a number of advantages. Thus, it can be shown to be exact for the Translog GDP function, it allows for a complete multiplicative decomposition of nominal and real GDP, and it is consistent with state-of-the-art measures of total factor productivity that typically rely on the Törnqvist aggregation. Estimates for a sample of 26 countries are reported. We find that the Laspeyres quantity index still used by the statistical agencies of most countries tends to underestimate real growth. Over the 1960–1996 period, the cumulated shortfall was as much as 13.4% of GDP in the case of Japan.     

A Coincident Index,Common Factors,and Monthly Real GDP*

The Stock–Watson coincident index and its subsequent extensions assume a static linear one‐factor model for the component indicators. This restrictive assumption is unnecessary if one defines a coincident index as an estimate of monthly real gross domestic products (GDP). This paper estimates Gaussian vector autoregression (VAR) and factor models for latent monthly real GDP and other coincident indicators using the observable mixed‐frequency series. For maximum likelihood estimation of a VAR model, the expectation‐maximization (EM) algorithm helps in finding a good starting value for a quasi‐Newton method. The smoothed estimate of latent monthly real GDP is a natural extension of the Stock–Watson coincident index.     

中国土地出让金与GDP关系研究

研究目的:揭示土地出让金与GDP之间的作用性质和作用程度。研究方法:Granger因果检验,广义脉冲响应和方差分解分析。研究结果:Granger检验结果显示土地出让金收入对GDP存在单向的显著可信的Granger因果关系,广义脉冲响应和方差分解结果显示,土地出让金对GDP的影响大于GDP对土地出让金的影响。研究结论:土地出让金对GDP有着显著的单向作用,GDP对土地出让金有较强的依赖性;而经济波动对土地出让金的影响不明显。     

Google data in bridge equation models for German GDP

Interest in the use of “big data” when it comes to forecasting macroeconomic time series such as private consumption or unemployment has increased; however, applications to the forecasting of GDP remain rather rare. This paper incorporates Google search data into a bridge equation model, a version of which usually belongs to the suite of forecasting models at central banks. We show how such big data information can be integrated, with an emphasis on the appeal of the underlying model in this respect. As the decision as to which Google search terms should be added to which equation is crucial —- both for the forecasting performance itself and for the economic consistency of the implied relationships —- we compare different (ad-hoc, factor and shrinkage) approaches in terms of their pseudo real time out-of-sample forecast performances for GDP, various GDP components and monthly activity indicators. We find that sizeable gains can indeed be obtained by using Google search data, where the best-performing Google variable selection approach varies according to the target variable. Thus, assigning the selection methods flexibly to the targets leads to the most robust outcomes overall in all layers of the system.     

A new coincident index of business cycles based on monthly and quarterly series

Popular monthly coincident indices of business cycles, e.g. the composite index and the Stock–Watson coincident index, have two shortcomings. First, they ignore information contained in quarterly indicators such as real GDP. Second, they lack economic interpretation; hence the heights of peaks and the depths of troughs depend on the choice of an index. This paper extends the Stock–Watson coincident index by applying maximum likelihood factor analysis to a mixed‐frequency series of quarterly real GDP and monthly coincident business cycle indicators. The resulting index is related to latent monthly real GDP. Copyright © 2002 John Wiley & Sons, Ltd.     

Globalization and business cycle transmission

The paper uses long-run GDP data for developed countries drawn from Maddison [Maddison, A. (2003). The world economy—Historical statistics. Paris: OECD Development Centre] to generate deviation cycles for the period from 1870 to 2001. The cyclical deviates are examined for their bilateral cross-correlation values in three separate periods, those of the first globalization wave (1870–1914), the period of the “bloc economy” (1915–1959) and for the period of the second globalization (1960–2001). Cluster analysis is applied and the McNemar test is used to test for the relative coherence of alternative groupings of countries in the three periods. The bloc economy period emerges as one that features some well-defined sub-global clusters, where the second globalization period does not, the first globalization period lying between the two in this respect. The second globalization period shows a generally higher level of cross-correlations and a lower variance than the other two periods. The features uncovered suggest that the second globalization period is indeed one that comprises a more inclusive world economy than ever before.     

社会物流总费用变化趋势与影响因素分析

文中通过对国家发展和改革委员会、国家统计局以及中国物流与采购联合会联合发布的2004-2013年全国物流运行情况通报,对社会物流总费用与GDP、社会物流总额等之间的关系进行分析,得出了其变化趋势特征,并分析出影响社会物流总费用偏高的因素,从而为降低我国社会物流总费用寻找出突破口。     

绿色GDP测算与可持续发展

当今社会经济迅速发展,我国的GDP呈逐年增长趋势,但我国的GDP增长,在一定的程度上是以牺牲自然资源和破坏环境带来的。这并不符合现在国际上提出的“绿色GDP”增长的概念。并且我国的风沙化、沙漠化、水土流失、空气和水资源的污染等,环境问题也日益严重。要实现我国经济的可持续发展,就要实行绿色GDP的测算。本文将通过一系列观点和事例,来论述绿色GDP测算和可持续发展战略之间的关系。     

Trends and Cycles in GDP

The recent experience in the UK of substantial growth in GDP following the recession of the early 1980s has led to renewed interest in the measurement and explanation of business cycles. Development of economic as well as econometric theory has improved our ability both to measure the cycle more accurately and to offer a better explanation of its behaviour. In this Briefing Paper we present an analysis of these two developments.     

Identifying relevant and irrelevant variables in sparse factor models

This paper considers factor estimation from heterogeneous data, where some of the variables—the relevant ones—are informative for estimating the factors, and others—the irrelevant ones—are not. We estimate the factor model within a Bayesian framework, specifying a sparse prior distribution for the factor loadings. Based on identified posterior factor loading estimates, we provide alternative methods to identify relevant and irrelevant variables. Simulations show that both types of variables are identified quite accurately. Empirical estimates for a large multi‐country GDP dataset and a disaggregated inflation dataset for the USA show that a considerable share of variables is irrelevant for factor estimation.     

物流成本占GDP比重中的产业结构因素

近几年物流业的发展备受关注，我们经常看到这样的报道：我国物流成本占GDP比重高达16．7％甚至。而美国只10％左右，于是就会直观地说中国远远落后于发达国家，物流成本管理水平与发选国家有较大差距。无可否认，中国物流成本管理水平确实根落后．但是直接比较两个国家的物流成本占GDP的比重能否反映出这两个国家物流成本的真实差距。本文作者认为，物流成本占GDP比重还受产业结构的影响，即当两个国家产业结构有较大差异时．即使这两国物流成本管理水平属同一水平，物流成本占GDP的比重也会有较大的差别．所以比较前提应是两国产业结构相似。而产业结构有较大差异的两国．用另外一个指标更合理——产业产值——物流成本弹性，即比较相同产业中的物流成本占产业产值的比重。     

Nowcasting German GDP: Foreign factors,financial markets,and model averaging

This paper develops a nowcasting model for the German economy. The model outperforms a number of alternatives and produces forecasts not only for GDP but also for other key variables. We show that the inclusion of a foreign factor improves the model’s performance, while financial variables do not. Additionally, a comprehensive model averaging exercise reveals that factor extraction in a single model delivers slightly better results than averaging across models. Finally, we estimate a “news” index for the German economy in order to assess the overall performance of the model beyond forecast errors in GDP. The index is constructed as a weighted average of the nowcast errors related to each variable included in the model.     

Temporal causality between house prices and output in the US: A bootstrap rolling-window approach

This paper examines the causal relationships between the real house price index and real GDP per capita in the US, using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and real GDP per capita, covering the period 1963:Q1 to 2012:Q2. The full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from the real house price index to real GDP per capita. A wide variety of tests of parameter constancy used to examine the stability of the estimated vector autoregressive models indicate short- and long-run instability. This suggests that we cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach to examine the causal relationship between these two variables. Using a rolling window size of 28 quarters, we find that while causality from the real house price to real GDP per capita occurs frequently, significant, but less frequent, evidence of real GDP per capita causing the real house price also occurs. These results imply that while the real house price leads real GDP per capita, in general (both during expansions and recessions), significant feedbacks also exist from real GDP per capita to the real house price.     

中国物流管理水平与社会物流成本的定量关系

先假设中美两国的产业结构相似,用假设后中美社会物流成本占GDP比重的差为指标,分析两国物流管理水平的差距,得出指标的平均值为2.5%。再用灰色关联分析2001~2010年两国的GDP与社会物流成本构成成分间的关联程度,得出中国的物流管理成本与GDP关系最不密切。定量说明了理性看待中国物流管理水平对社会物流成本的影响,具有重要现实意义。     

可持续发展与绿色GDP

在衡量经济增长的各项指标中,人们普遍首选GDP,而现行的GDP体现不了当今社会倡导的可持续发展的思想。针对这一问题,本文在论述了可持续发展思想及现行GDP及其缺陷的情况下,简要阐述了绿色GDP的概念及其核算的内容及方法。     

湖南省区域经济发展空间差异分析

文章以湖南省14个市州为主要区划单元,对2001年和2009年各市州的人均GDP、人均GDP的偏离率等进行对比分析,得出湖南区域经济呈现由东自西递减的空间格局以及产业结构不合理的结论,并提出相应对策。     

Regional trade agreement and foreign direct investment

This paper investigates the relationship between regional trade agreements, such as the NAFTA, and FDI. Using a fixed-effects gravity model to estimate OECD panel data spanning 1982–1997, we learn that trade integration encourages FDI. We find specific evidence for each of the NAFTA member countries—Mexico, Canada and the United States. In addition, we find evidence that FDI will rise with host and parent country GDP and fall with distance.