Answer

Abstract

Following the global economic recession of between 2007 and 2009, economic policy uncertainty along with its effects upon economic recovery has gained attention and interest in media, policy-making circles, and academic (Baker et al., 2016)). Given this backdrop, this study aimed at explaining how a shock to economic policy uncertainty affects China and the U.S. To achieve this aim, the paper studied the degree to which economic policy uncertainty shocks in major economies (for this study, the U.S.) affects real economic activities in emerging economies (for this study, China). Following Baker et al.’s model, the researchers constructed a newspaper-based economic policy uncertainty index for China for the period between 1998 and 2016. The researchers estimated international spillovers of uncertainty and determined large spillovers from major economies to China. Additionally, the researchers showed that an increase in a country’s local EPU leads to tight/restricted monetary conditions, and lower vacancy posting and investment, which dampens the economy’s domestic output growth. Similarly, the researchers examined the impact of uncertainty regarding economic policy uncertainty on the U.S.’s direct FDI, imports, and exports.  Uncertainty over internal and domestic was found to significantly affect the country’s international flow of investment, services, and goods. Generally, the study indicated that the EPU has negative effects upon American and Chinese economies.

Table of Contents

1. Introduction. 3
2. Literature Review.. 5
3. Conclusion. 11

References. 12

How Does A Shock To Economic Policy Uncertainty Affect China And the US?

1.      Introduction

The globalization process has significantly led to economies across the world to be inter-connected more than in times past. For this reason, a shock associated with a particular economic policy in an economy/country instantly gets carried to other economies/countries. Cesa-Bianchi et al. (2014) reason that this is often more pronounced when the countries/economies from which shock is coming are the principal role players in defining the world’s economic activity. Uncertainty in economic policy can have negative impacts upon economic growth and recovery. Investors and consumers are likely to hesitate in investing and spending when they sense greater uncertainty in a country’s economic policy atmosphere (Claeys et al., 2018; Makarova, 2018). Chi and Li (2017) add that economic uncertainty equally tends to negatively affect a country’s monetary marketplace since valuations of assets are likely to fall. The economy of China, which is a long reliable spring of economic growth, is steadily slowing, a condition that has created uncertainty within the global marketplaces. Challenges in China, the second largest world’s economy, can crease global economic growth and growth in general, a big issue at a time when geopolitical and weak oil prices concerns are equally clouding up the outlook (Nantob, 2015). These statements highlight the growing significance of China’s economy for the global economy. In fact, since the employment of the structural marketplace reforms in the year 1978, China is considerably integrated into the global marketplaces. Specifically, China’s imports is currently representing about 10% of the world’s imports, its output accounts for 10% of the world’s production, and its investments constitute about 10% of the globe’s investments (McDermott, 2017). Nonetheless, during the last 10 years, a protracted period of unpredictability has appeared due to the universal economic crisis between 2000 and 2008. Examples include the 2012 United States (U.S.) “fiscal cliff”, the 2011 Eurozone debt crisis, the 2015 Chinese stock marketplace crash, the 2016 Brexit, and the more lately the political crisis in South Korea and Brazil to mention but a few (Makarova, 2018). Those events could affect macroeconomic activities not just for China’s economy, but equally for a wide variety of other associated economies.  According to Chi and Li (2017), unpredictability of future growth prospects in countries that are emerging, particularly in China, adds more concerns to the future evolution of the global macroeconomy. It, therefore, appears crucial to better the understanding of spillover effects of the Chinese unpredictability shocks, which is measured by the economic policy uncertainty index of Baker et al. (2016) upon real activity for a sample of economies/countries that are representing China’s main economic partners, like the U.S.  To this end, this paper discusses how a shock to economic policy uncertainty affects the U.S. and China.

This study is motivated by a number of factors. First, most papers that have been done on this topic emphasize that unpredictability is a crucial determinant of an economy’s business cycle. For example, autarkic frameworks that were developed by Caggiano et al. (2017a) and Mumtaz and Theodoridis (2015) showed that uncertainty shocks can impeded the economy’s macroeconomic activities with a negative implication upon the economy’s economic growth, private investment, unemployment, and consumption (Cesa-Bianchi et al., 2014; Claeys et al., 2018). Second, most literature regarding the global spillover impacts of uncertainty principally consider the U.S. as the distinct “exporter” of uncertainty (Nantob, 2015; McDermott, 2017). Regarding this, Makarova (2018) and Chi and Li (2017) found out that the U.S. uncertainty shocks pollute other economies globally like the European region and China, among other economies. By putting more attention upon uncertainty spillovers emerging from China on some developed countries (the U.S.), this paper will significantly contribute to extant literature and bridge a crucial gap. Additionally, the study will show that the effects of international uncertainty shocks are country-specific. Alexopoulos and Cohen (2015) and Benigno et al. (2011) found robust dissimilarities between developing and developed countries in uncertainty shocks’ face. This study will attempt to harmonize the dissimilarities in these studies’ findings by policy prescriptions, behaviour of households and firms, as well as the characteristics of local marketplace. Third, studies have shown that spillover impacts of uncertainty are especially crucial during recessions (Li et al., 2010; Caldara et al., 2016; Christiano et al., 2014). The conversely, during economic depressions, uncertainty spillovers seem to be much more restricted.  To establish the veracity of these findings, this present study will use the Vector Autoregressive (SVAR) model. Lastly, the choice of the U.S. is informed by the work of Colombo (2013) which shows that interconnects between main trading partners are a crucial explanation regarding transmission avenues of uncertainty spillovers. Specifically, the U.S. is China’s largest trading partner, representing 20% of China’s total exports according a 2015 report (Alexopoulos & Cohen, 2015).

2.      Literature Review

Standard macroeconomic theories suggest that a rise in uncertainty within an economy may cause a non-permanent fall in the economy’s econometric activity. Reasoning from a firm’s viewpoint, irreversible investment in a country provides the usual mechanism via which transformations in uncertainty impact the country’s economic activity (Claeys et al., 2018). This way, exogenous changes in uncertainty or volatility within an economy lead to the deferment of irreversible investment and thus a decline in the economy’s present level of economic activity (Nantob, 2015). However, as volatility is resolved, investment arrangements are brought forward besides the fact that a country’s economic activity level starts to recuperate. Reasoning from the household’s viewpoint, under some assumptions, increased volatility about an economy’s future dividends and labour income inflows induces households to raise their individual precautionary savings by minimizing their consumption, and thus demand (Bekaert et al., 2013; Caldara et al., 2016; Christiano et al., 2014). But again, as volatility or unpredictability recedes, households’ consumption recovers. Monetary frictions offer an extra mechanism via which volatility may impact an economy, generally via a rise in the risk premium (Li et al., 2010; Krol, 2018; Luk et al., 2017). 

Several studies have been conducted on the effect of economic policy uncertainty on various countries. One such is the study by Cesa-Bianchi et al. (2014) which, using China as a developing economy, aimed at determining the degree to which economic policy uncertainty shocks in developed economies affects real economic activities in developing ones. The researchers first compiled economic policy uncertainty index for China between 1998M4 to 2017M4 using Baker et al.’s (2016) model to enumerate the number of associated news articles. This choosing of this method was informed by a range of reasons. It captures a wide array of uncertainty in a well-timed manner. The measure has high frequency besides the fact that it can go back to several decades back. The researchers were then able to compare their economic policy uncertainty index with another proxy volatility based upon realized stock marketplace uncertainty.

Secondly, the researchers examined to what extent uncertainty shock in China are ‘imported’ from across the world. China’s economy is sensitive to economic growths and developments in the U.S., as well as highly associated with other principal economies like Japan and European Union (EU). Informed by the study by Bekaert et al. (2013), the researchers adopted a non-structural network connectedness methodology to investigate international spillovers of economic policy uncertainty from these developed economies to China.

Thirdly, the researchers proceeded to analyze the effect of economic policy uncertainty upon macro-financial conditions. They employed a standard Cholesky methodology to help them identify an unpredictable shock to economic policy uncertainty.

Several findings were made by the researchers. The researchers found out that their uncertainty index were broadly consistent with economic concepts of previous studies since they showed that spikes were noted in China’s economy during major universal happenings like the 2001 9/11 terrorist attack, the 1997-1998 Asian economic crisis, the 2007 U.S. subprime crisis, the 2008 Lehman brothers’ bankruptcy, the 2011 downgrading of the U.S. sovereign credit rating, as well as the 2008 deepening of the European sovereign debt crisis, findings which are supported by Krol (2018), Luk et al. (2017), Makarova (2018), and Chi and Li (2017). The study also indicated that the uncertainty index seemed to be sensitive to China’s local events, like the 2003 outbreak of severe acute respiratory syndrome (SARS), the 2006 discussions regarding the implementation of services and goods tax, and the 2016 weakening of China’s domestic economic atmosphere.  This is in agreement with the findings of studies by Nantob (2015), McDermott (2017), and Krol (2018).

To compare their uncertainty index’s forecasting power for real gross domestic product (GDP) growth against that of the stock marketplace uncertainty, Nantob’s (2015) simple univariate forecasting model was employed. The model is as shown below:

∆_ℎ𝑌_𝑡+ℎ = 𝛼 + (ℎ_𝑖=1)+ 𝛾₁𝑈𝑛𝑐𝑒𝑟𝑡_𝑡 + 𝜔_t

Where ∆_ℎ𝑌_𝑡+ℎ =  ln ( ) = h-quarters growth of real,𝑈𝑛𝑐𝑒𝑟𝑡_𝑡=economic policy uncertainty index or the achieved Hang Seng Index Volatility (𝐻𝑆𝐼𝑣𝑜𝑙.).

To identify the principal drivers of China’s economic uncertainty, the researchers followed Klößner and Sekkel (2014) and Luk et al. (2017)’s network approaches to carry out a spillover assessment of uncertainty. Specifically, they used Luk et al. (2017)’s methodology and estimated a VAR model with p lags as follows:

𝑌_𝑡 = ∅₁𝑌_𝑡−1 + ⋯ + ∅_pY_t-p+ €_t

Where €_t = an independent and identically distributed shock and ∅₁…∅_p = coefficient matrix of the lag terms, and Y_t= a vector of economic policy uncertainty indices of China and its principal trading partners.

To determine the actual impacts of economic policy uncertainty shocks, the researchers also used the aforementioned SVAR model, which is represented as:

B₀X_𝑡 = C + B₁X_t−1 + B₂X_t−2 + … + B_pX_t−p+ €_t

Where c = a vector of constants, B₁, B₂ … B_p = coefficient matrices, and €_t = a vector of structural innovations. X_t comprises of the following endogenous variables: economic policy uncertainty, financial condition index (FCI), real private investment growth, growth in posting of private industry vacancy, and real GDP growth.

From the study, it was found out that there were sizeable spillovers of economic policy uncertainty from developed economies to China. Additionally, it found out that a shock to volatility has a negative effect upon China’s real output development and growth rate. Additionally, using the SVAR model, the researchers showed that an increase in China’s local economic policy uncertainty results in tight economic circumstances, and lowers vacancy posting and investment, which dampen local output growth and development.

In another study to determine how far a rise in uncertainty affecting China could be transmitted to other economies, Benigno et al. (2011) investigated the possible spillovers that originated from a shock to China’s economic policy uncertainty to developed economies, like the U.S., Japan, Euro Area, and South Korea, along with developing economies, like Russia and Brazil. Using the above SVAR model, the researchers found crucial asymmetries in the reactions to China’s uncertainty shocks of macroeconomic variables particularly on the U.S., South Korea, and Euro Area.

The study found out that the study’s econometric models unveil crucial asymmetries in the reactions of the study’s sample of areas/countries to China’s policy-associated volatility shocks. Therefore, the researchers realized that volatility contagion from the Chinese economy is significant during global economic recessionary stages. For example, the U.S.’s uncertainty level increases of approximately 10% during recessions whereas nearly no response is visible during economic expansions. With an effect of about 15%, areas/countries like the Euro Area, Brazil, and South Korea significantly respond much more to China’s shock. Secondly, the study showed that Chinese uncertainty shocks significantly hamper domestic macroeconomic activity principally during bad seasons/times. Generally, when hitting a country during recessions, an anticipated spike in China’s uncertainty is anticipated to induce a decline in local industrial production as well as exports along with a rise in unemployment (with the exception of Asian economies). Third, the study found out that the contribution of an economic policy uncertainty shock from the Chinese economy to local macro-variables variations is greater and larger during good seasons/times. These findings are supported by Makarova (2018), Colombo (2013), and Alexopoulos and Cohen (2015).

Caggiano et al. (2017b) also did a study that concentrated upon the role of economic policy uncertainty within open marketplaces. Caggiano et al. (2017b) found out that variations in the volatility of the actual interest rate at which small and open emerging marketplaces borrow to exert impacts upon actual activity in open economies like Ecuador, Argentina, Brazil, and Venezuela. They found out that shocks to the unpredictability of financial policy shocks, productivity shocks, and inflation target shocks realized in the U.S. are crucial propellers of several real and nominal indicators in the G7. The researchers proposed a policy-balance theory of exchange rate determination depending upon the interaction between financial policy and uncertainty, and showed that their theoretical model is capable of replicating the stylized details that are identified with their SVARs. The researchers estimated that a one standard deviation (SD) in the unpredictability of the shock to the U.S.’s real GDP could lead to a fall in the United Kingdom’s (U.K.) GDP of 1% compared to trend as well as a 0.7% rise in the U.K.’s consumer price index (CPI). Colombo (2013) and Mumtaz and Theodoridis (2015) also studied about the interactions between trade, real activity, and policy uncertainty, and they found out that policy uncertainty is a crucial determining factor affecting investment decisions and trade, a finding that is also supported by Klößner and Sekkel (2014) and Gilchrist et al. (2014). This present paper, therefore, adds to literature by unveiling the impacts of the economic policy uncertainty shocks originating in the U.S. exert with regard to China’s business cycle. 

Working with a standard real commercial cycle model, a study by Gilchrist et al. (2014) about the impacts of uncertainty shocks upon real activity as forecasted by micro-founded dynamic stochastic general equilibrium models, showed that uncertainty shocks are expansionary since they exert a negative impact upon families’ wealth, raise the marginal utility for people’s consumptions and, thus, labour supply, which ultimately raises output. A different viewpoint was given by Klößner and Sekkel (2014) who found out that a larbour marketplace model that is featuring matching fictions forecast a negative effect upon input by unpredictability shocks. This negative impact, according to the researchers, is associated with an optimal “wait-and-see” methodology that is implemented by companies due to the lower anticipated value of filled openings in the presence of uncertainty. According to the researchers, this lead companies to post a lower number of job openings, which eventually leads to a lower number of job matches on the labour marketplace equilibrium. The study adds that sticky prices can magnify this impact owing to the negative effect of uncertainty upon aggregate demand, and subsequently, upon companies’ relative prices, whose decline signify an even lower job vacancies’ number posted in symmetry.

3.      Conclusion

From the foregoing literature, it can be deduced that trade policy uncertainty and economic policy uncertainty negatively affects FDI inflows into the U.S., and U.S.’s exports and imports. When economic policy uncertainty is high, foreign and domestic businesses prefer to wait as opposed to spend their resources in investing and expanding sales within or without the U.S. owing to the fact that more than 50% of the U.S.’s imports are intermediate ones, and since lower FDI limits formation of capital, GDP falls, thus lowering living standards of people living in the U.S. Using China, as example of countries suffering the effects of economic policy uncertainty in the U.S., the paper used economic policy uncertainty index to show that there are statistically significant spillovers of economic policy uncertainty from the U.S. and other major economies to China, and that a shock unpredictability has a negative upon China’s real output growth rate.