Forecasting GDP all over the world using leading indicators based on comprehensive survey data

Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and instantaneous available source of leading indicators, the ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 countries and three country aggregates separately. We come up with three major results. First, for more than three-fourths of the countries or country-aggregates in our sample, a model containing one of the major WES indicators produces on average lower forecast errors compared to a benchmark model. Second, the most important WES indicators are either the economic climate or the expectations on future economic development for the next six months. And third, adding the WES indicators of the main trading partners leads to a further increase in forecast accuracy in more than 50% of the countries. It seems therefore reasonable to incorporate economic signals from the domestic economy’s main trading partners.     

Sunspots, GDP and the stock market

A correlation has been observed between the US GDP and the number of sunspots as well as between the Dow Jones Industrial Average and the number of sunspots. The data cover 80 years of history. The observed correlations permit forecasts for the GDP and for the stock market in America with a future horizon of 10 years. Both being above their long-term trend they are forecasted to go over a peak around Jun-2008.     

Forecasting GDP at the Regional Level with Many Predictors

In this study, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden‐Württemberg) and Eastern Germany. We overcome the problem of a ‘data‐poor environment’ at the sub‐national level by complementing various regional indicators with more than 200 national and international indicators. We calculate single‐indicator, multi‐indicator, pooled and factor forecasts in a ‘pseudo‐real‐time’ setting. Our results show that we can significantly increase forecast accuracy compared with an autoregressive benchmark model, both for short‐ and long‐term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP.     

中国的GDP及其若干统计问题

本文探讨了GDP统计方法的基本概念和局限性,特别是从历史的角度分析了GDP核算体系对日益增长的无形投资(intangibleinvestment)和知识经济的忽略,并在此基础上对中国经济及其在全球经济中的地位和影响作了重新评估。文章指出,现行GDP统计方法没有包括非市场经济、地下经济和闲暇活动;低估了我国劳务等产业创造的价值及其增长潜力;无法追踪企业在技术革新、产品设计、品牌打造和员工培训这些无形资产方面的投资;忽略了我国经济中迅速增加的知识经济成份,特别是教育投资成份。文章的结论是,由于历史、文化和制度诸方面的原因,这些忽略和低估对处于转型过程中的发展中国家中国来说要远远大于发达国家和其他发展中国家,因此,我国的实际经济总量及其增长率,特别是增长潜力要远高于官方的统计数字。     

Divisia monetary aggregates and US GDP nowcasting

ABSTRACT

This article nowcasts US quarterly real GDP growth rate with dynamic factor model (DFM) using Divisia Monetary Aggregate Index, Divisia M1, M2, M3, and exploits information from a large, unbalanced panel data. GDP nowcasting is evaluating the current quarter GDP given the available economic data up to the point when the nowcasting is conducted. GDP data is published quarterly with a substantial lag, while many monetary and financial decisions are made at a higher frequency. Therefore, nowcasting GDP has become an increasingly important task for central banks. This article uses DFM to nowcast GDP, compares the nowcasting results from DFM with the simple sum monetary aggregate M1, M2, M3, to the Model with weighted corresponding Divisia Index, then calculates the contributions of the Divisia Monetary index to US GDP nowcasting.     

Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach

This paper uses the panel data of energy consumption and GDP for 82 countries from 1972 to 2002. Based on the income levels defined by the World Bank, the data are divided into four categories: low income group, lower middle income group, upper middle income group, and high income group. We employ the GMM-SYS approach for the estimation of the panel VAR model in each of the four groups. Afterwards, the causal relationship between energy consumption and economic growth is tested and ascertained. We discover: (a) in the low income group, there exists no causal relationship between energy consumption and economic growth; (b) in the middle income groups (lower and upper middle income groups), economic growth leads energy consumption positively; (c) in the high income group countries, economic growth leads energy consumption negatively. After further in-depth analysis of energy related data, the results indicate that, in the high income group, there is a great environmental improvement as a result of more efficient energy use and reduction in the release of CO₂. However, in the upper middle income group countries, after the energy crisis, the energy efficiency declines and the release of CO₂ rises. Since there is no evidence indicating that energy consumption leads economic growth in any of the four income groups, a stronger energy conservation policy should be pursued in all countries.     

Political stability and growth: An application of dynamic GMM and quantile regression

This paper studies the effect of political stability on economic growth by taking 120 developing countries over the period of 1996–2014. We apply relatively advanced dynamic two step system-GMM and quantile regression. Political stability is found to be a key determinant of economic growth. More importantly, political instability (or risk) is found to be higher in the OIC countries and is a deterrent to economic growth. Also, for the lower and middle income OIC countries, political instability appears to affect economic growth more severely perhaps due to the absence of strong economic and political institutions. Moreover, political instability is also found to be significantly higher in the oil-dependent OIC countries. Notably, political instability is likely to affect growth through the channels of investment and human capital accumulation in the developing countries. Finally, the impact of political stability and political instability on growth is found to be equally distributed across the OIC countries with higher or lower growth level. Therefore, the development of political and economic institutions along with human capital development is recommended for all the developing countries in general and the OIC countries in particular.     

广东省潜在GDP增长率测算及预测

就广东省潜在GDP增长率进行了测算,使用HP滤波法和生产函数法得到的结果分别为9.1%和8.4%,从生产函数法的计算过程中,认为广东在1978—2012年的经济具有规模报酬不变的特征,并就当前情况作了分析。在对未来预测上,考虑到生产函数的各要素间可能存在相互关系而使用向量自回归进行。并以本轮金融危机的延续时间为变量,分别测算不同情况下未来五年和十年的平均增长率。     

Uncertainty and risk analysis of the Langrun Chinese GDP Forecast: Fan Charts revisited

In this paper, we develop a fan chart methodology for Chinese economic growth to incorporate uncertainty analysis into the gross domestic product growth forecast. Using the ‘Langrun Forecast’ project results exclusively, we estimate the density distribution for Chinese gross domestic product growth forecasts and build corresponding fan charts for the first time. Our analysis shows that the fan chart method effectively highlights the overall uncertainty and balance of risks surrounding Chinese gross domestic product growth, especially during the past international financial crisis between 2007 and 2009. Wallis' interval forecast test is conducted to evaluate the performance of the produced fan charts, and the results indicate that our forecasts perform well for the period being investigated.     

Exploring GDP growth volatility spillovers across countries

This study takes a portfolio approach to investigate GDP growth volatility spillovers among 120 countries of the world during the 1960–2017 period. Based on the ratios of growth rate to standard deviation, we rank these countries in pools of high-, midsize-, and low-income growth. Using a spillover index that is based on variance decompositions under a vector autoregressive framework, we analyze the sources of growth volatility dynamics in the world in terms of volatility proportions from and to others. We find that high-income growth countries are net transmitters, while low-income growth countries are net recipients of growth volatility. We also find that it takes several years for low-income growth countries to absorb growth shocks of global nature. Overall, our analyses illustrate the importance of partnership in risk sharing as it is related to portfolio strategies and risk management.     

Forecasting the Consumer Confidence Index with tree-based MIDAS regressions

The macroeconomic literature has recently uncovered the importance of the consumer confidence variations at driving business cycles. However, it remains a challenge to predict changes in agents'confidence by exploiting the information from ultra high-frequency sentiment data extracted from social media. Based on the mixed data sampling (MIDAS) literature, we propose a new MIDAS method that introduces regression tree-based algorithms into the MIDAS framework. Our method is more flexible at sampling high-frequency lagged regressors compared to existing MIDAS models with tightly parametrized functions of lags. In an out-of-sample forecasting exercise for the Consumer Confidence Index, our results reveal that (i) the proposed procedure exploits more fully the information from historical sentiment data and (ii) our method substantially improves the forecast accuracy and confirms the role of social media at affecting the consumer confidence.     

1990—2010年中国人口预期寿命与人均GDP的相关关系及其变化特征

预期寿命是反映人口寿命水平的重要指标,人均GDP是反映经济发展的重要指标。采用相关分析和回归分析对中国1990—2010年市域、县域两个尺度的预期寿命与人均GDP的关系进行分析,结果表明:人均GDP对预期寿命具有显著正向影响,但累积影响强于即时影响;人均GDP超过3000~5000元后,其对预期寿命的影响开始出现边际递减效应;人均GDP对预期寿命的影响强度在空间分布上自东向西增强。由于经济相对发达的东部地区人均GDP对预期寿命的贡献率要小于经济相对落后的西部地区,因此,今后东部地区应通过完善社会保障、优化卫生资源配置、倡导健康生活方式等途径进一步提高预期寿命,西部地区则应大力发展区域经济,努力提高生活水平,以尽快缩小与东部地区预期寿命的差距。     

我国出口贸易额与国内生产总值关系研究

以我国1990—2012年的出口贸易额和国内生产总值进行实证分析,并得出结论:我国出口贸易额与国内生产总值成正相关,并且出口贸易总额对国内生产总值的边际系数为0.28。据此,对这种关系提出了一些相关建议。     

Testing the null hypothesis of no regime switching with an application to GDP growth rates

This paper presents tests for the null hypothesis of no regime switching in Hamilton’s (Econometrica 57:357–384, 1989) regime switching model. The test procedures exploit similarities between regime switching models, autoregressions with measurement errors, and finite mixture models. The proposed tests are computationally simple and, contrary to likelihood based tests, have a standard distribution under the null. When the methodology is applied to US GDP growth rates, no strong evidence of regime switching is found. I thank Don Andrews, Peter Phillips, Yuichi Kitamura, Anat Bracha, Patrik Guggenberger, Orit Whiteman and three anonymous referees for useful comments and suggestions.     

中国GDP年度序列数据的周期性分解与制度阐释:1978-2005

国内生产总值(GDP)是体现一个国家的经济实力、发展水平和生活水准的综合性指标.将GDP年度序列数据中的周期趋势分离出来,不仅是一个统计技术问题,更是一个研究经济运行规律的方法问题.按定基指数调整后的真实GDP年度序列在去除时间趋势之后存在明显的周期性波动,这种周期波动与我国转型阶段制度供给的阶段性高度吻合,制度供给是经济系统运行周期波动的内生性因素.     

Forecasting China's inflation in a data-rich environment

Inflation is one of the most recent critical issues facing China. To improve inflation forecasts within China, this study investigates the predictive ability of three dimension reduction techniques used in a data-rich environment: Principal Components Analysis (PCA), Sliced Inverse Regression (SIR), and Partial Least Squares (PLS) applied in the Factor-Augmented Autoregression (FAAR) model proposed by Stock and Watson (2005). Varied macroeconomic data from China between January 1998 and December 2009 are obtained to construct factors for use by three different techniques. The performance of different dimension reduction methods depends on forecasting horizons, the number of factors chosen, and the number of slices for SIR. The empirical study finds that the FAAR model with an optimal number of PCA factors outperforms the other model in out-of-sample inflation forecasting in China.     

中国宏观经济总量的实时预报与短期预测——基于混频数据预测模型的实证研究

季度GDP的走势与波动不仅会影响政府的财政收支、企业的盈利和财务状况,甚至还会影响家庭和个人的收入与支出,是宏观经济总量预报、预测与分析的重中之重。传统的宏观经济总量预测模型是基于同频数据进行的,高频和超高频数据必需处理为低频数据,这不仅忽略了高频数据信息的变化,还影响了模型预报和预测的及时性,降低了模型的预测精度。本文将混合数据抽样模型(MIDAS)用于中国季度GDP的预报和预测,实证研究表明,出口是造成我国金融危机时期经济增长减速的主要因素,MIDAS模型在中国宏观经济总量的短期预测方面具有精确性的比较优势,在实时预报方面具有显著的可行性和时效性。     

我国M_2/GDP的动态增长路径、货币供应量与政策选择

本文试图求解我国M2/GDP的动态增长路径,并对与此相关的金融政策选择进行分析。研究发现,我国M2/GDP的变动路径具有Logistic曲线的基本形状,将经历先加速上升后增长速度逐渐减缓,最终趋于稳定状态的变化过程。本文估算了我国M2/GDP的增长上限及其变化拐点。研究还发现,M2/GDP的上升并不必然意味着通胀压力加大,只有M2/GDP偏离动态增长路径时,才会对通货膨胀产生影响。据此本文估算了2005年货币供应量的合理区间。本文认为,应继续实施稳健货币政策,合理确定货币总量增长速度,继续推进体制性改革等措施确保经济金融的稳定运行。     

Nowcasting Chinese GDP: information content of economic and financial data

This article applies the factor model proposed by Giannone, Reichlin, and Small (2005 Giannone, D., Reichlin, L. and Small, D. 2005. “Nowcasting GDP and inflation: The real time information content of macroeconomic data release”. In Finance and Economic Discussion Series 2005–42, Washington, DC: Board of Governors of the Federal Reserve System.  [Google Scholar]) on a large data set to nowcast (i.e. current-quarter forecast) the annual growth rate of China's quarterly GDP. The data set contains 189 indicator series of several categories, such as prices, industrial production, fixed asset investment, external sector, money market, and financial market. This article also applies Bai and Ng's criteria (2002) to determine the number of common factors in the factor model. The identified model generates out-of-sample nowcasts for China's GDP with smaller mean-squared forecast errors than those of the random walk benchmark. Moreover, using the factor model, we find that interest rate data is the single most important block of information to improve estimates of current-quarter GDP in China. Other important blocks are consumer and retail prices data and fixed asset investment indicators.