Asian Trade Integration and the Decoupling Debate of Business Cycles

＂Decoupling＂ refers to the divergence of business cycles among different countries, while ＂re-coupling＂ corresponds to the convergence or the synchronization of business cycles among different countries. The decoupling debate is popular in the field of economics, especially after global financial crisis. As trade integration increased among Asian countries, business cycle synchronization among these countries was expected to increase through trade transmission. The aim of this study is to discover whether there has been decoupling or convergence of business cycles through various trade channels. However, theoretically, increased trade can lead to business cycle synchronization either rising or falling. Inter-industry trade resulting in higher specification will induce less synchronized business cycles, while intra-industry trade could lead to increased business cycle synchronization. Thus, it is important to distinguish between intra- and inter-industry trade flows. Both correlation and dynamic factor models are utilized to study the evolution of global business cycle linkages. Results indicate that the world factor has become less important in explaining macroeconomic fluctuations from sub-period 1961-1984 to sub-period 1985-2007, while regional factors do not play an important role in explaining aggregate volatility, with the expectation of consumption. Overall, the explanatory power of country factors increases. Domestic consumption and domestic investment variances are more driven by country and idiosyncratic factors than by the world factor, contrary to the output growth fluctuations. Regional factors and country factors also play a more prominent role in explaining gross import fluctuations than in explaining gross exports. Results cast doubt on the strong forms of both the decoupling and the re-coupling hypothesis.

Chinese Business Cycles Identified by Coincident Indexes

In reference to the method of the Conference Board,the coincident indexes for China are constructed from a sample period between January 1990 and May 2012 and by51 chosen component indicators.The resulting coincident indexes have higher correlations with gross domestic product(GDP) growth rates than the China Economic Monitoring and Analysis Center(CEMAC) coincident index over the sample period between February2005 and May 2012.The peaks and troughs of the growth rates in several indicators are identified.The total number of peaks and troughs in the resulting coincident index is the same with the CEMAC coincident index.Unfortunately,these troughs don't signify recessions in the Chinese economy because the financial system has not seen a negative growth rate over the specific sample periods.The impacts of the Southeast Asian Financial Crisis and subprime mortgage crisis on the business cycle could be dated via a smoother index from HP filtering to the coincident index.

Recent progress in econophysics： Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like ＂intelligence＂ remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents＇ intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Regional Clustering and Synchronization of Provincial Business Fluctuations in China

In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.

The Credit Cycle and the Business Cycle in the Economy of Turkey

This study examines econometric relationships between bank lending and the business cycle in Turkey. Firstly, the cyclical components of the real GDP and real bank loans were determined using time series. A cointegration analysis and a vector error-correction model with quarterly data were used for period of 1987：01-2013：03. The results of cointegration analysis indicate that there is a single stable long-run equilibrium relationship between real bank loans and macroeconomic variables. The response of bank loans to GDP shocks is positive. Bank loans have pro-cyclical character in Turkey.

The stationary solution of a random dynamical model

This paper studies the stationary probability density function（PDF） solution of a nonlinear business cycle model subjected to random shocks of Gaussian white-noise type. The PDF solution is controlled by a Fokker–Planck– Kolmogorov（FPK） equation, and we use exponential polynomial closure（EPC） method to derive an approximate solution for the FPK equation. Numerical results obtained from EPC method, better than those from Gaussian closure method, show good agreement with the probability distribution obtained with Monte Carlo simulation including the tail regions.

Enterprises＇ inventory Fluctuations Useful in Monitoring the Economic Cycle

It has been demonstrated by both domestic and international theories and empirical studies that inventory fluctuations are cyclical in nature, which makes it useful in monitoring how the economy is currently operating. Based on a survey o foyer 5,000 enterprises conducted by the People＇s Bank of China, we have attempted to compile a finished goods inventory index of the 5,000 enterprises. Through our analysis, we are able to determine that the 5,000 enterprises inventory index displays the basic features of pro-cyclicality and fits the business cycle with a lag of one quarter. Currently, the inventory index shows signs of declining after five consecutive months of increases, indicating that the expansion of enterprises＇production is temporarily slowing down.

Impact of Fiscal Policy on Economy After Accession to the Euro Area： The Case of Poland

The impact of Polish fiscal policy on economy after accession to the euro area is analyzed in the article. It was found that government spending financed by distortionary taxation affects output in a different way than in case of government spending financed by bonds. Poland＇s accession to the Economic and Monetary Union will reduce the possibility of increased government spending financed by bonds, which in light of the presented model will greatly reduce the possibility of stimulating the economy through fiscal policy.

Business Cycle Asymmetry in China:Evidence from Friedman's Plucking Model

Friedman＇s plucking model of business fluctuations suggests that output cannot exceed an upper limit, but it is occasionally ＂plucked＂ downward below trends as a result of economic recessions. This paper investigates China＇s business fluetuations using quarterly real GDP data for the period 1978 2009. Our results show some evidence supporting Friedman＇s plucking model. We find that a ceiling effect of real output exists, and that negative asymmetric shocks significantly affect the transitory component, which captures the plucking downward behavior during the recession. The results also suggest that the basic asymmetric unobserved component model is not appropriate for directly modeling China＇s real output because the business＂ cycle is inaccurately measured, but it works quite well when considering a structural break in the second quarter of 1992. The results reveal that although China＇s economy strengthened in the second quarter of 2009, it is essential for China＇s government to take further positive and effective measures to maintain sustainable development of the economy.

The Business Cycle and Profitability of Trading Strategies

Recent studies show that investor participation in the stock market rises during economic expansion and drops in economic recession. When investor participation is high, investors＇ cognitive and behavioral biases are likely to have a strong influence on stock prices. We consider four trading strategies that are based on well-known market anomalies and examine their profitability under different economic conditions. For all four strategies, the portfolios that are formed in the months when the economy is expanding obtain significant profits, whereas the portfolios formed in economic recession months are not profitable. This finding is robust to different ways of classifying recession months.

Business Cycle in China since the Lehman Crisis:Interaction among Macroeconomic Policy,Economic Growth and Inflation

The major objectives of China＇s macroeconomic policy are to stabilize economic growth and inflation, which, in turn, are important factors determining key prices, such as the policy interest rate, the renminbi exchange rate and stockprices. In a framework that distinguishes different phases of the business cycle based on whether the current period＇s economic growth rate and inflation rate are above or below their ＂＇normal＂ values, this paper analyzes the interaction among macroeconomic policy, economic growth and inflation in China since the Lehman crisis, and the implications for these key prices. The path of China＇s economy indicates that stimulus measures taken by the government during the recession phase and tightening measures implemented during the overheating phase have helped minimize the fluctuation over the business cycle. Our analysis shows that Chinese authorities tend to rely more on adjusting the exchange rate than the interest rate to stabilize the economy. Comparing with conditions at the time of the post-Lehman recession, the current slowpace of economie growth in China may reflect not only weakening demand, but also a lowerpotential growth rate associated with the arrival of the Lewis turning point.

Hot Money and Business Cycle Volatility:Evidence from China

This paper investigates the link between hot money and business cycle volatility in China from January 1997 to December 2009. Using the structural vector error correction model we find a considerable degree of long-run cointegration and bidirectional causality effects between hot money and business cycle volatility. The speculative shocks are found to temporarily promote China＇s economic growth, but also to exacerbate business cycle volatility. The liquidity shock stemming from hot money is shown to be the primary factor responsible for the significantly enhanced fluctuation in business cycles during the most recent global financial crisis period This could be detrimental to the smooth operation of financial markets. Therefore, informing future policies, it is critical for policy-makers to take precautions against the speculative factors.

Why Has the Business Cycle in China Become More Stable in the Twenty- first Century？

The purpose of this paper is to answer two questions： first, what are the causes of the stability of the Chinese business cycle in the twenty-first century？ Second, what are the sources of volatility for the Chinese economy in the twenty-first century？ Using statistical analysis and constructing a multi-equation structural macro-economic model, we find the answer to the first question depends almost totally on domestic factors, including the stability of domestic demand shock and the automatic stabilization mechanism existing in the credit market. As to the second question, the greatest sources of volatility are foreign and domestic demand shocks, with the former having a greater effect on the volatility of GDP while the latter has a greater effect on the CPI. Another finding is that traditional monetary policy targeting money supply has little effect on the stability of GDP and CPI. One policy suggestion is that a domestic stimulus policy to stabilize aggregate demand is still vital against the background of the global crisis; another is that to get rid of negative impact of globalization upon our economy, we need to rely more on urbanization rather than industrialization and need to re-adjust the economic roles of different regions within China.

On business cycle forecasting

We develop a recession forecasting framework using a less restrictive target variable and more flexible and inclusive specification than those used in the literature.The target variable captures the occurrence of a recession within a given future period rather than at a specific future point in time(widely used in the literature).The modeling specification combines an autoregressive Logit model capturing the autocorrelation of business cycles,a dynamic factor model encompassing many economic and financial variables,and a mixed data sampling regression incorporating common factors with mixed sampling frequencies.The model gene rates significantly more accurate forecasts for U.S.recessions with smaller forecast errors and stronger early signals for the turning points of business cycles than those gene rated by existing models.

Is political business cycle an enemy to human development?Empirical evidence from Africa

Extant literature has argued that,with major extension of democracy since the 1990s,political business cycle has become more intense and has made African political systems more fragile.In light of this,this paper examines both the existence of African political business cycles and their impact on human development.It confirms the existence of political business cycles in Africa.Estimates of a panel fixed effects and system-GMM regression techniques for 38 African countries from 1990 to 2015 also suggest that such cycles worsen human development in African countries.This finding is consistent if we limit our analysis to various sub-regions of Africa,and also at two different income levels.

A new broom sweeps clean:is there a Chinese-style political business cycle?

Politics is an important cause of economic growth and fluctuations.We present a new Political Business Cycle(PBC)Theory based on the background of recent Chinese economic transformation and government behaviors,explore the economic impact of the National Congress of the Communist Party of China(CPC),the National People’s Congress(NPC)and Chinese People’s Political Consultive Conference(CPPCC)and how they shape and influence the behaviors of local government officials.Based on 1994-2012 inter-provincial panel data of China and using SYS-GMM and LSDVC,we find that there are significant effects in China of PBC and government administration change.Changes in government administration influence the economic behaviors of local governments,which in turn influence local economic development through fiscal decentralization and political promotion tournament.These effects are sustained and robust.In this paper we offer an economic explanation for the Chinese proverb“a new broom sweeps clean,”and try to verify the Chinese-style Political Business Cycle(CPBC).We provide new ideas for further improving the functions of government,optimizing macroeconomic control,and preventing personnel changes in the government from overheating the economy.

An Estimated DSGE Model for Business Cycle Analysis in China

A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that the monetary authority takes an aggressive stance to the current inflation pressure （there is a significant lagged response）, while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, overall our estimated model can successfully reproduce the stylized facts from actual data of Chinese business cycles and frequently can even outperform those forecasts from an unconstrained VAR.

ESTIMATING MULTI-COUNTRY PROSPERITY INDEX: A TWO-DIMENSIONAL SINGULAR SPECTRUM ANALYSIS APPROACH

With the development of the global economy, interaction among different economic entities from one region is intensifying, which makes it significant to consider such interaction when constructing composite index for each country from one region. Recent advances in signal extraction and time series analysis have made such consideration feasible and practical. Singular spectrum analysis （SSA） is a well-developed technique for time series analysis and proven to be a powerful tool for signal extraction. The present study aims to introduce the usage of the SSA technique for multi-country business cycle analysis. The multivariate SSA （MSSA） is employed to construct a model-based composite index and the two dimensional SSA （2D-SSA） is employed to establish the multi-country composite index. Empirical results performed on Chinese economy demonstrate the accuracy and stability of MSSA-based composite index, and the 2D-SSA based composite indices for Asian countries confirm the efficiency of the technique in capturing the interaction among different countries.

Construction and Analysis of Common Foreign Trade Cycle Based on MS-VAR:An Empirical Study of Global Experience

This paper proves the co-movement of foreign trade in different countries or areas which belong to ten economic regions by MS-VAR model.The studies show that trade crisis lags behind economic crisis and spreads from the core of the economic crisis to its periphery which is closely-related with it.The trade crisis corresponding to the US subprime crisis spreads faster than before,which has struck worldwide foreign trade.In order to get the main factors affecting trade crisis,the authors construct composite indices which are proxies of economic growth and price levels of internal and external regions.The results of logistic and linear panel models show that economic growth affects more to trade cycle than price level.The results of panel models with dummy variable of trade crisis show that the outside economic growth do bad to the recovery of internal foreign trade during trade crisis corresponding to Mexican peso crisis,the Asian financial crisis and the Russian debt crisis,while the opposite is true during the internet bubble burst and the US subprime crisis.

QUANTUM FINANCIAL ECONOMICS——RISK AND RETURNS

Financial volatility risk and its relation to a business cycle-related intrinsic time is addressed through a multiple round evolutionary quantum game equilibrium leading to turbulence and multifractal signatures in the financial returns and in the risk dynamics.The model is simulated and the results are compared with actual financial volatility data.