Do governmental policy interventions help urban economic recovery? Experimental evidence from China's provinces governance amid the COVID‐19 pandemic

Abstract

By examining China's province‐level data, this paper uses governmental intervention theory to investigate the extent to which governmental policy interventions alleviate the impact of the COVID‐19 pandemic on local economic growth. Results suggest that stronger government intervention during COVID‐19 pandemic boost the economic recovery, and the effectiveness of governmental policy interventions is contingent on pandemic severity and local economic endowment. Specifically, facilitating effect of government intervention on economic growth is effective in all provinces, and the impact of government intervention is more pronounced in the province with more diagnosed cases, a high level of marketization and fiscal income.

Abbreviations

CHI

containment and health index

ESI

economic support index

GRI

government response index

IGDP

industrial gross domestic productivity growth rate

IGDP2

industrial GDP growth rate compared with the same month in last year

PPI

producer price index

SI

stringency index

1. INTRODUCTION

On March 11, 2020, the World Health Organization (WHO) declared COVID‐19 as a global pandemic. Up until July 18, 2022, COVID‐19 had infected over 560 million confirmed cases worldwide. ¹ In order to block the spread of COVID‐19 and guard public health in cities and regions, many countries issued strict measures such as “lockdown, social distancing, border closures” to control the spread of pandemic. Many businesses, most notably in the service industry, have been required to shut down. The pandemic has caused a systemic shock to the global economy. To alleviate the effects of the pandemic, many countries have implemented an “economic stimulus” package.

How will the pandemic‐control measures affect the economy? Will the economic stimulus measures work? How to strike a balance between controlling pandemic and economic recovery? These questions of COVID‐19 are not yet clearly understood. Previous literature investigates the significant economic after‐effects of COVID‐19 (Altig et al., 2020; Atkeson, 2020; Gourinchas, 2020; Jordà et al., 2022; Tang, 2021), and points that the COVID‐19 has been associated with subsequent large economic damage. Without doubt, a pandemic like COVID‐19 would have a sharp impact on economic, at the same time, the containment policies worsen the economic recession. Several researchers investigated to understand the necessity of “lockdown, social distancing, border closures” measures and its functioning mechanisms (Zhang et al., 2020). Furthermore, prior literature points the severe social‐economic cost of lock‐down (Baldwin & Weder, 2020; Jordà et al., 2022; Kelso et al., 2013; Wang et al., 2021).

Policymakers need to implement substantial targeted fiscal, monetary, and financial market measures to help due to the severe economic fallout (Baldwin & Weder, 2020; Furman et al., 2020). Although the economics of the coronavirus epidemic is different with financial crises, but some of the fallout will follow a similar pattern. As long as governments act quickly to contain the economic fallout, the long‐term effects on the economy will be less severe than the financial crisis (Odendahl & Springford, 2020). Besides, unlike a routine economic shock, the disturbance to aggregate demand and supply come together because of COVID‐19, and the markets break down altogether. So should policy respond on multiple fronts to attenuate potential falls in aggregate demand and supply and market failures (Baldwin & Weder, 2020).

In this paper, we try to present a comprehensive dissection of the impact of the governmental policy interventions on the economy, the function mechanism of governmental policy interventions during the public health emergencies, and analysis the appropriate way for the government to balance the relationship between the economy and anti‐pandemic measures.

The COVID‐19 pandemic is detrimental to all countries' economic regardless of their political systems and levels of economic development (Ludvigson et al., 2020). Governmental policy interventions have been widely utilized in most countries effected by the pandemic, including US, UK, and the European Union countries. The national governments have already responded with a variety of fiscal countermeasures, including the efforts to cushion income losses, incentivize hiring, expand social assistance, guarantee credit, and inject equity into firms. These measures have prevented widespread firm bankruptcies and have partially helped employment to rebound (IMF, 2020).

During Covid‐19 pandemic, most citizens have been required to self‐quarantine, been in compliance with strict “social distancing” policies and almost the whole country was shut down (Qiu et al., 2020; Zhang et al., 2020), which has caused massive economic impairment. China implements a series of invervention policy and achieves fast economic recovery. Significantly, it took China only three months to control the pandemic and achieved few domestic new daily cases. Thus, how to implement appropriate anti‐pandemic policies is a pivotal issue.

Faced with the shock of the COVID‐19 pandemic, the Chinese government has implemented strict anti‐pandemic policies, but at the same time issued a series of public policies, such as quantitative easing, to alleviate the impact of COVID‐19 on economic development. As regards monetary policy, the Chinese government provided 300 billion RMB in loans with low interest rates and issued over 30 policies to provide market liquidity (Xinhua News, 2020). As regards fiscal policy, the government issued 34 trillion RMB in investment in new infrastructure to promote economic recovery. In addition, regional government also implemented many indirect policies, such as consumption/shopping vouchers for citizens, in order to promote consumption. All these policies have played a crucial role in China's economic recovery, and the recovery in China has been faster than expected. China was the only expanded economy among major economies in the world in 2020 (IMF, 2020), and made a breakthrough in GDP of hundred trillion (101,598.6 billion yuan; NBSC, 2021). China's return to growth has been stronger than expected due to sizable, swift, and unprecedented fiscal, monetary, and regulatory responses (IMF, 2020). China's experience could provide lessons for other countries to tackle the pandemic.

The 31 provinces of mainland China serve as an appropriate setting to gauge the extent to which government policy interventions could alleviate the adverse impact of anti‐pandemic measures on local economic growth. These provinces have implemented different policies, which is ideal for us to examine the effects of different policies. With heterogeneous local pandemic conditions and economic fundamentals and yet homogeneous political and legal contexts, these provinces present us with a natural laboratory to investigate the impact of different policy interventions on the local economic recovery.

Our results indicate that although anti‐pandemic measures impede economic development significantly, governmental policy interventions are instrumental to provincial economic recovery. Our further analyses further indicate that facilitating effect of government intervention on economic growth is effective in all provinces, and the effect achieves better results in provinces with higher COVID‐19 cases, higher fiscal income or higher level of marketization.

This study has the following contributions: (1) Our empirical analysis shows that government policy promotes economic recovery after the pandemic. Thus, this paper not merely contributes to prior literature on the impact of government fiscal measures and monetary measures, but also contributes to the literature concerning the economic consequences of government intervention, specifically during a special period. (2) Although there are previous studies investigating how public health emergencies affect economics (Reitz, 1988), there is little research into the role of government during a pandemic. This study enriches studies concerning the public health emergencies and economics. (3) Our study adds to the existing literature about the influence factors on economic growth. Our study contributes to understanding how the pandemic and government interventions have affected economic growth. (4) Our study investigates the impact of both the anti‐pandemic measures and economic stimulation policies, thus our study might provide policy implications to enable the government to balance economic development and anti‐pandemic measures.

2. THEORY AND HYPOTHESES

Economic growth is the consequence of the interaction between the economic system of internal operations and external disturbance. As a kind of random and uncertain external disturbance to the economy, the pandemic has impaired both supply and demand, lowered production efficiency, and may even have changed the economic cycle (Fornaro & Wolf, 2020; Gong et al., 2020; Gourio, 2008). On the demand side, many people have not been willing to leave their homes and prefer reducing their consumption (Briscese et al., 2020; Wilson et al., 2020). On the supply side, factories have been unable to operate normally due to anti‐pandemic measures and production costs have increased as a result (Fornaro & Wolf, 2020; Guerrieri et al., 2022). Therefore, the COVID‐19 pandemic has lowered both demand and production, causing economic imbalance. During the pandemic, governments have implemented anti‐pandemic measures (O’Flynn, 2021), such as social distancing and restrictions in catering and travel. These measures could end the pandemic but could also cause great harm to the economy (Eichenbaum et al., 2020; Rahman et al., 2020).

Governmental intervention theory is an essential way to handle public health emergencies (Brusentsev & Vroman, 2017; Gao & Yu, 2020). Government intervention outsource form the Keynesianism. To address the economic crisis in the 1930s, Keynes proposed that governments should implement appropriate fiscal policy interventions in the economy. Keynesianism was instrumental in promoting the economic recovery of the USA (Wolff & Resnick, 2012). In the 1980s, new Keynesian economics suggested governments should implement both monetary and fiscal policies to intervene in the economy in order to maintain a stable economy. Nowadays, fiscal policies are widely utilized by most countries during financial crises. Based on governmental intervention theory, this study analyzes the effects of the Chinese government's policies during the COVID‐19 pandemic.

Whether governments should intervene in the economy is a heated debate (Landau, 1983; Ram, 1986; Rubinson, 1977; Samuelson, 1997; Smith, 1904; Stigler, 1983), while most researchers agree that public policy is the key to recovery from economic crisis (Ansell et al., 2021; Brusentsev & Vroman, 2017; O’Flynn, 2021). As the invisible hand, the market plays a crucial role in economic development, but the market is not always efficient (Mankiw, 2015). Based on governmental intervention theory, appropriate public policy could improve economic efficiency when the market loses control (Liou, 2013). During the pandemic, the Chinese government has issued a series of policies to promote economic recovery.

First, according to governmental intervention theory, appropriate public policy could improve economic efficiency when market has failed. Since the market could not provide the public with goods, the government played a crucial role in providing these goods (Samuelson, 1972), infrastructure, and met the public requirement. During the COVID‐19 pandemic, the Chinese government provided free testing and treatment for all Chinese citizens. These public goods and services were available to every citizen and strengthened public confidence in combating the pandemic. The anti‐pandemic services and products were non‐competitive, as well as non‐exclusive, and were a typical public good. Only the government could supply them. As such, these public goods and services have played a crucial role in tackling the pandemic.

Second, the market could not provide full employment and the COVID‐19 pandemic has impeded supply and demand. On the supply side, the pandemic has impaired the physical health of employees and has increased labor cost, leading to a higher level of unemployment. On the demand side, the pandemic has caused huge losses for the service industry, and citizens have reduced their consumption, thus causing a reduction of labor demand. In order to alleviate the impact of the pandemic, the Chinese government has issued many policies to promote the resumption of work and lower firms' operating costs. These measures have alleviated unemployment and have sustained economic stability. Thus, when the market has struggled to maintain high levels of employment, government intervention can allocate resources effectively and adjust the labor market, eventually leading to full employment.

Third, government intervention has had a direct effect on economic growth. Investments, consumption, and exportation have been three key drivers of this growth. In terms of investments, the Chinese government has issued 34 trillion RMB in investment in new infrastructure, thus promoting investments substantially. In terms of consumption, the government has distributed shopping vouchers and has encouraged “e‐commerce”, while also removing restrictions imposed on the “street vendor” economy. These policies have stimulated citizens' consumption and have promoted economic recovery. As regards exportation, the Chinese government has provided low‐cost loans and tax benefits for firms, alleviating operational pressures. Furthermore, due to the pandemic outbreak in other countries, China has become the largest medical supplier as a country which can now operate normally. These policies have exerted a substantial effect on economic recovery.

Finally, government intervention could alleviate economic recession and promote economic stability. The COVID‐19 pandemic has hindered firms' normal operations and has caused great damage to many industries, especially the service industry. During the pandemic, the Chinese government has taken effective measures to maintain the supply of daily essentials and has promoted the resumption of work. On the one hand, the Chinese government has postponed and waived certain taxes and the payment of other fees and has encouraged firms to resume operations and provided low‐cost loans for firms. On the other hand, the Chinese government has utilized national deposits to moderate the price of daily necessities and stabilize market supplies. These policies have effectively eased economic recession and promoted economic recovery.

In short, we proposes the main hypothesis:

H 1

Government intervention can promote economic recovery.

3. DATA AND METHODOLOGY

3.1. Data and sample selection

To investigate the impact of government intervention policy on the economic recovery, we utilize China 31 provinces data as the research sample. ² We employ the monthly economic statistics as main data. We acquired the province‐month level information from National Bureau of Statistics of China (NBSC). ³ Our data are from February 2019 to December 2021 as our research sample. Our sample do not include January because the National Bureau of Statistics of China do not release the cumulative industrial GDP growth rate in January (Wang et al., 2012).

3.2. Variables

3.2.1. Measurement for the economic growth

To measure the economic growth, we utilize the industrial gross domestic productivity growth rate as the main dependent variables. The GDP for each province is only available for the quarterly data and there are only industrial GDP data for the monthly data (Liu et al., 2002). Next, industrial GDP is a key component of GDP and in the pandemic industrial GDP could better measure the GDP in each province China. Besides, to make our variables comparable to previous years, we employ the cumulative industrial GDP growth rate (IGDP) as the main dependent variable.

In addition, we still employ the industrial GDP growth rate compared with the same month in last year (IGDP2), cumulative industrial firms' sales growth rate (Sales), cumulative profits growth rate of industrial firms (Profit) as the alternative measure to carry out the robust check.

3.2.2. Measurement for the government intervention

We use the Oxford COVID‐19 Government Response Tracker (OxCGRT) to indicate the direct, indirect intervention and anti‐pandemic strength. The Oxford COVID‐19 Government Response Tracker (OxCGRT) from Oxford University can be used to measure Government response (Lee et al., 2021; Zhang, Liang, et al., 2021). The OxCGRT started collecting data on COVID‐19 government responses of China in late January 2021. Data are collected from publicly available sources such as news articles and government press releases and briefings. This dataset records government responses to COVID‐19 in 31 provincial‐level jurisdictions, all of which receive policy guidelines or recommendations from national authorities, such as the National Health Commission and the Ministry of Finance. It records the day‐by‐day policy changes in these subnational jurisdictions since 1 January 2020 (Zhang, Hale, et al., 2021). The dataset can be accessed on their GitHub repository. ⁴

Concerning about the data availability, we finally only choose four polices as the main indexes: government response index (GRI), containment and health index (CHI), stringency index (SI), as well as economic support index (ESI).

OxCGRT includes 21 indicators for the government response, and incorporates eight containment and closure policy indicators (C1–C8), four economic policy indictors (E1–E4), eight health system indicators (H1–H8), and three vaccination policies (V1–V3). GRI is consists of all these indicators, CHI includes all the C and H indicators, SI contains all C indicators as well as H1, and ESI incorporates all E indicators. To investigate the impact of government intervention on economic recovery, we also employ the data in 2019 as the baseline group and set the value of GRI, CHI, ESI and SI as zero for the data in 2019.

3.2.3. Measurement for the control variables

To estimate the impact of pandemic and government intervention on economic development, this paper still controls the impact of capital invest (Capital) and producer price index (PPI).

Capital measures the growth rate of total fixed assets investment in that month, compared with the same month of last year. Investment in fixed assets is a precondition for the economic growth of a country (region), an important way to optimize the industrial structure, and an important driving force to achieve sustainable and healthy economic development (NBSC, 2007). The impact of the fixed assets investment to the increasing of GDP is positive (Zhang et al., 2014). Fixed assets investment has become an important force driving economic development in China's economic growth structure (Qin et al., 2006). ⁵ To mitigate the epidemic's impact and withstand the downward economic pressure, the government enacts policies for greater investment and increasing infrastructure investment (Aganbegyan, 2020; Liu et al., 2020). ⁶ Nationwide, the Chinese government putted forward a series of economic stimulus plans to promote market recovery. ⁷ From the perspective of local governments, some provinces accelerated the construction of major projects, and lots of regions added the number and investment amount of key construction projects during the year. Some provinces ramped up steady investment, and focusing on a number of major investment projects. The data of Capital are collected from the NBSC.

PPI measures the Producer Price Index growth rate, compared with the same month of last year. Producer Price Index is considered the most important indicators to measure the economic condition (Hakimipoor et al., 2016), and Producer Price Index has a relatively important impact on economic growth (Shi & Wang, 2016). The data of PPI are collected from the NBSC.

In addition, we control the province fixed effects and month fixed effect to control the unobservable factors which is time‐invariant and province‐invariant. All the main variables definitions are shown in Table 1.

TABLE 1.

Variable definition

Variable	Definition
IGDP	The cumulative industrial gross domestic productivity growth rate
IGDP2	Industrial GDP growth rate compared with the same month in last year
Sale	The cumulative total sales growth rate
Profits	The cumulative profits growth rate
Capital	The cumulative growth rate of fixed assets investment
PPI	Producer price index growth rate, compared with the same month of last year
GRI	The government response index in OxCGRT database, covering all indicators in OxCGRT database
CHI	The containment and health index in OxCGRT database, covering all C and H indicators in OxCGRT database
SI	The stringency index in OxCGRT database, including all C indicators and H1 indicator in OxCGRT database
ESI	The economic support index in OxCGRT database, including all E indicators in OxCGRT database
Marketization	NERI index of marketization of China's provinces 2018 report (Wang et al., 2019)
Income	The financial income of a province government, which is total fiscal income in 2019
Cases	The cumulative diagnosed cases a province has in that month

3.3. Methodology

In our analysis, we employ the province‐level panel data to investigate the impact of government intervention on the economic growth. Our regression model is shown as Equation (1). We utilize panel fixed effect model to run the regression of Equation (1). It takes some time for the policy to exert effect on the economy recovery, so we take a lead for the dependent variable for 3 months. In addition, we also employ the 6 months lead for the IGDP.

$${\text{IGDP}}_{\mathrm{i},t+3}={\beta }_0+{\beta }_1{\text{Intervention}}_{\mathrm{i},\mathrm{t}}+{\text{Controls}}_{i,t}+{\delta }_i+{\delta }_t+{\epsilon }_{\mathrm{i},\mathrm{t}}$$ (1)

In the Equation (1), ${\beta }_0$ represents the constant term, ${\beta }_1$ denote the impact of governmental policy interventions. $\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}$ represent the control variables. ${\delta }_i$ and ${\delta }_t$ denote the province fixed effects and month fixed effects. A positive and significant ${\beta }_1$ represents that government intervention policy could facilitate the economic recovery.

4. EMPIRICAL ANALYSES

In this section, we present the figure for the GDP growth at first. Next, the summary statistics for the main variables are shown. Finally, we carry out the multi‐linear regression.

4.1. Industrial GDP growth rate by different month

We present the industrial GDP growth rate by each month, excluding January, from February 2019 to December 2021 in Figure 1. There is a large decrease of the industrial GDP growth rate in February 2020, implying that industrial GDP growth experiences large reduction in February 2020. This result implies that the COVID‐19 outbreak is detrimental to the economic growth and cause a great economic decrease. After 2020 February, the IGDP begins to rise up, demonstrating the China economy recovery from the pandemic.

FIGURE 1.

Historical industrial gross domestic productivity growth from 2019 to 2021.

4.2. Summary statistics

This paper presents the summary statistics for the main variables in Table 2. The average IGDP is 6.89, indicating that the average industrial GDP growth rate is 6.89%.

TABLE 2.

Description statistics

Variable	N	Mean	S.D.	Min	Max
IGDP	1023	6.89	9.76	−17.70	41.30
Capital	1023	5.34	13.22	−34.90	53.80
PPI	1023	102.70	8.01	90.70	135.10
GRI	1023	37.20	27.05	0	76.56
CHI	1023	39.79	28.91	0	83.33
ESI	1023	19.05	23.70	0	75
SI	1023	34.58	26.23	0	83.33

Besides, the correlation coefficient between GRI and IGDP is 0.280, implying that stronger policy intervention promotes the economic growth. To alleviate this concern, we calculate the variance inflation factor for each regression model. In Table 3, the largest VIF is 1.25, which is smaller than 10. This result indicates that most of our regression results are not affected by the multicollinearity problems.

TABLE 3.

Pearson correlation analysis

	IGDP	Capital	PPI	GRI	CHI	ESI	SI
IGDP	1
Capital	0.355***	1
PPI	0.163***	0.252***	1
GRI	0.280***	0.0370	0.266***	1
CHI	0.296***	0.071**	0.315***	0.996***	1
ESI	0.0250	−0.277***	−0.270***	0.628***	0.555***	1
SI	0.233***	−0.00800	0.226***	0.986***	0.982***	0.618***	1

***p < 0.01, **p < 0.05, *p < 0.1.

4.3. Baseline result

At first, we investigate the impact of governmental policy interventions on the industrial GDP growth and present the regression results in Table 4. All the models pass the 1% level of F test, implying that our models are significant. The R ² are higher than 0.18, showing that our model has at least 18% explanatory power.

TABLE 4.

Impact of economic stimulation policy on economic recovery

Variables	(1)	(2)	(3)	(4)
	GRI	CHI	ESI	SI
	IGDP	IGDP	IGDP	IGDP
GRI	0.097***
	(9.476)
CHI		0.093***
		(9.649)
ESI			0.081***
			(6.218)
SI				0.089***
				(8.606)
Capital	0.278***	0.274***	0.302***	0.286***
	(11.332)	(11.159)	(12.149)	(11.633)
PPI	0.001	−0.017	0.154***	0.020
	(0.038)	(−0.579)	(5.497)	(0.673)
Constant	1.696	3.519	−12.029***	0.276
	(0.565)	(1.157)	(−4.021)	(0.092)
Observations	1023	1023	1023	1023
Adjusted R‐squared	0.221	0.223	0.184	0.207
Month FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
F	105.4***	106.1***	90.07***	95.74***

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

The coefficient of GRI is 0.097 and significant, showing that the industrial GDP growth would be larger if a province has stronger government response index. More specifically, one standard deviation (SD) increase of GRI contributes to about 38.05% (0.097 × 27.05/6.896) industrial economic growth rate, relative to the average level. Besides, the coefficients of CHI, ESI, and SI are positively significant, implying that stronger government intervention during COVID‐19 pandemic boost the economic recovery.

In addition, Capital present positive significant coefficients, implying that higher capital investment could promote the economic growth. However, PPI has no significant coefficient, indicating that the production purchasing index has no pronounced effect on economic growth.

4.4. Subsample analysis

Previous results verify the promoting effect of government intervention on economic recovery. Thus, this paper furtherly examines impact of these policies in different provinces.

4.4.1. Impact of diagnosed cases

Government can use Diagnosed Covi‐d19 cases to assess the risk of community transmission of COVID‐19 of the province (Jia et al., 2020). Diagnosed COVID‐19 cases somewhat reflect the local seriousness of COVID‐19 pandemic.

Government strengthens the “slant” force degree of policy toward the areas suffer the severe damage of COVID‐19 pandemic (CSRC, 2020; General Office of the State Council, PRC, 2020). That is, governments may make rapid and accurate risk assessments based on diagnosed COVID‐19 cases, and plan the allocation of limited resources. In areas where the epidemic situation is more serious, the epidemic prevention and control is more severe, the local government intervention is stronger, and the policies and implementation are harder.

Thus, the local seriousness of COVID‐19 pandemic affects governmental policy interventions during COVID‐19, and the local seriousness of COVID‐19 pandemic might also affect the economic recovery. Thus, we intend to investigate whether pandemic severity reshapes the relationship between government intervention and economic recovery.

On the one hand, we utilize the number of diagnosed COVID‐19 cases to evaluate the pandemic level.  These data from Chinese Stock Market and Accounting Research database (CSMAR).

We divide the sample into two parts based on median number of the diagnosed COVID‐19 cases in Table 5. In Table 5, no matter in which column, the regression passes 1% level F test and R squares are higher than 0.153, implying that our regression model is significant and has a relatively good explanatory power. GRI, CHI, ESI, and SI are all present significantly positive coefficient, implying that facilitating effect of government intervention on economic growth are effective in all provinces. Furthermore, the coefficients of GRI, CHI, ESI, and SI are higher in the provinces with more diagnosed COVID‐19 cases, and the coefficient differences are statistically significant. These results show that the impact of government intervention is more pronounced in the province with more diagnosed cases.

TABLE 5.

Subsample analysis: the impact of diagnosed cases

Variables	Low	High	Low	High	Low	High	Low	High
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
GRI	0.062***	0.136***
	(4.769)	(9.093)
CHI			0.061***	0.128***
			(4.948)	(9.091)
ESI					0.047***	0.129***
					(2.849)	(6.902)
SI							0.056***	0.127***
							(4.305)	(8.326)
Capital	0.178***	0.394***	0.176***	0.386***	0.193***	0.433***	0.184***	0.403***
	(8.154)	(9.793)	(8.060)	(9.611)	(8.563)	(10.340)	(8.415)	(9.899)
PPI	0.065*	−0.098*	0.053	−0.129**	0.148***	0.198***	0.075**	−0.065
	(1.842)	(−1.749)	(1.467)	(−2.253)	(4.668)	(3.565)	(2.176)	(−1.157)
Constant	−3.374	9.613*	−2.236	12.707**	−10.700***	−18.131***	−4.135	6.805
	(−0.933)	(1.703)	(−0.609)	(2.220)	(−3.070)	(−3.125)	(−1.148)	(1.203)
Observations	495	528	495	528	495	528	495	528
Adjusted R‐squared	0.178	0.265	0.180	0.265	0.153	0.218	0.169	0.245
Month FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Diff (Low = High)	−0.0739***		−0.0673***		−0.0822***		−0.0707***
p value	0.00		0.00		0.00		0.00
F	52.42***	72.29***	53.03***	71.62***	49.31***	58.60***	51.04***	62.90***

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

4.4.2. Impact of fiscal income and marketization

First, compared with other countries in the world, China is a highly decentralized economy in which local governments largely have the right to make policies for local economic development and receive tax revenues from local economic growth (Xu, 2011). Fiscal income is closely related to fiscal policy (Yang et al., 2016), thus effect policy implementation.

The scope and quantity of public goods and services provided by the government in social and economic activities depend to a large extent on the abundant state of fiscal income. The higher fiscal income reveals higher local fiscal power. The abundant financial resources of the government can guarantee its various expenditures. Thus, the policy implementation effect, that is governmental policy interventions alleviating the impact of the COVID‐19 pandemic on local economic growth, might be reshaped by local government fiscal power.

Second, according to government intervention theory, appropriate public policy could improve economic efficiency when market has failed. The process of regional marketization is closely related to China's unbalanced and uncoordinated regional economic development (Shi & Wang, 2016). A triple process of marketization, globalization, and local government intervention constitute economic transition in China (He et al., 2008). In provinces with higher marketization level, the market order is more standardized, and the cost for local governments to implement industrial policies is lower (Sun & Xi, 2015). Thus, the policy implementation effect might be reshaped by local marketization level.

We employ a province's fiscal income as the proxy for fiscal power and marketization index as the proxy for marketization level. These data are acquired from the National Statistics Bureau of China and NERI index of marketization of China's provinces 2018 report (Wang et al., 2019).

We divide the sample based on the median value of fiscal income and marketization index. We present the subsample analysis in Tables 7 and 8. In Tables 7 and 8, all the results pass 1% F test and have a relatively higher R² (at least 18.4%), implying that our models are significant and have good explanatory power.

TABLE 7.

Subsample analysis: the impact of fiscal income

Variables	Low	High	Low	High	Low	High	Low	High
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
GRI	0.067***	0.149***
	(5.520)	(9.329)
CHI			0.066***	0.141***
			(5.763)	(9.341)
ESI					0.049***	0.136***
					(3.071)	(6.957)
SI							0.063***	0.141***
							(5.195)	(8.527)
Capital	0.176***	0.437***	0.172***	0.430***	0.200***	0.451***	0.182***	0.445***
	(8.965)	(10.056)	(8.776)	(9.926)	(9.930)	(9.851)	(9.343)	(10.005)
PPI	0.064**	−0.185**	0.051*	−0.222***	0.146***	0.196***	0.072**	−0.134*
	(2.113)	(−2.455)	(1.660)	(−2.877)	(5.016)	(2.916)	(2.413)	(−1.788)
Constant	−3.282	17.701**	−2.095	21.465***	−10.317***	−18.276***	−3.870	13.259*
	(−1.044)	(2.352)	(−0.659)	(2.790)	(−3.192)	(−2.612)	(−1.230)	(1.755)
Observations	495	528	495	528	495	528	495	528
Adjusted R‐squared	0.216	0.262	0.219	0.262	0.184	0.208	0.208	0.240
Month FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Diff (Low = High)	−0.082		−0.075		−0.087		−0.078
p value	0.00		0.00		0.00		0.00
F	65.29***	64.29***	66.27***	63.89***	61.29***	51.95***	64.20***	55.20***

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

TABLE 8.

Robust check: Industrial GDP growth rate compared same month in last year

Variables	(1)	(2)	(3)	(4)
	IGDP2	IGDP2	IGDP2	IGDP2
GRI	0.035***
	(5.406)
CHI		0.032***
		(5.175)
ESI			0.049***
			(6.330)
SI				0.036***
				(5.346)
Capital	0.031**	0.029**	0.048***	0.034**
	(2.348)	(2.225)	(3.501)	(2.578)
PPI	−0.094***	−0.099***	−0.026	−0.090***
	(−3.757)	(−3.894)	(−1.076)	(−3.623)
Constant	14.040***	14.570***	7.310***	13.651***
	(5.633)	(5.785)	(2.932)	(5.514)
Observations	930	930	930	930
Adjusted R‐squared	0.122	0.120	0.129	0.122
Month FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
F	11.75	10.99	15.10	11.47

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

In Table 6, GRI, CHI, ESI, and SI has smaller coefficients in the provinces with lower marketization index and these differences are statistically significant. These results illustrate that the positive influence of government intervention on economic recovery is stronger in the province with higher marketization. Thus, government should implement the intervention policy in the provinces with high marketization.

TABLE 6.

Subsample analysis: the impact of marketization level

Variables	Low	High	Low	High	Low	High	Low	High
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
GRI	0.057***	0.159***
	(4.946)	(9.668)
CHI			0.057***	0.150***
			(5.177)	(9.677)
ESI					0.040***	0.150***
					(2.669)	(7.355)
SI							0.052***	0.151***
							(4.581)	(8.909)
Capital	0.172***	0.439***	0.169***	0.432***	0.192***	0.454***	0.178***	0.449***
	(8.786)	(10.352)	(8.627)	(10.233)	(9.529)	(10.105)	(9.104)	(10.340)
PPI	0.069**	−0.220**	0.058*	−0.267***	0.137***	0.256***	0.078***	−0.171*
	(2.372)	(−2.442)	(1.961)	(−2.891)	(4.936)	(3.123)	(2.704)	(−1.888)
Constant	−3.625	21.053**	−2.617	25.785***	−9.361***	−24.351***	−4.224	16.666*
	(−1.198)	(2.336)	(−0.855)	(2.798)	(−3.044)	(−2.874)	(−1.399)	(1.837)
Observations	495	528	495	528	495	528	495	528
Adjusted R‐squared	0.214	0.268	0.217	0.268	0.187	0.214	0.207	0.246
Month FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Diff (Low = High)	−0.102		−0.093		−0.110		−0.099
p value	0.00		0.00		0.00		0.00
F	61.52***	69.87***	62.31***	69.60***	58.64***	55.25***	60.44***	60.91***

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

In Table 7, the results are similar to Table 6 and the coefficients of GRI, CHI, ESI, and SI are larger in the provinces with higher fiscal income, and these differences are significant at 1% level. These results demonstrate that the promoting effect of government intervention on economic growth is more pronounced in the provinces with higher fiscal income.

In a word, the local government should implement the government intervention in the provinces with high marketization or high fiscal income.

4.5. Robust check

We carry out a robust check by utilizing the industrial GDP growth rate compared with same month in last year (IGDP2), cumulative sales growth rate of industrial firms (Sale), and profits growth rate of industrial firms (Profits) as the alternative measurements for industrial GDP.

In Table 8, GRI, CHI, ESI, and SI have positive and significant coefficients, which are consistent with baseline results. These results indicate that government intervention policy could promote the economic recovery.

In Table 9, we employ the cumulative sales growth rate of industrial firms as the dependent variable, and GRI, CHI, ESI, and SI present the positively significant coefficients, verifying the robustness of our conclusion.

TABLE 9.

Robust check: Cumulative sales growth rate of industrial firms

Variables	(1)	(2)	(3)	(4)
	Sales	Sales	Sales	Sales
GRI	0.155***
	(10.884)
CHI		0.147***
		(10.934)
ESI			0.165***
			(8.597)
SI				0.140***
				(9.573)
Capital	0.421***	0.414***	0.475***	0.433***
	(13.232)	(13.050)	(14.070)	(13.548)
PPI	0.665***	0.639***	0.932***	0.697***
	(12.088)	(11.435)	(18.910)	(12.749)
Constant	−65.710***	−63.039***	−90.753***	−68.131***
	(−11.850)	(−11.213)	(−17.702)	(−12.279)
Observations	1023	1023	1023	1023
Adjusted R‐squared	0.418	0.417	0.401	0.403
Month FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
F	298.7	297.7	290.0	270.5

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

In Table 10, the cumulative profits growth rate of industrial firms (Profits) is set as the dependent variable, and GRI, CHI, ESI, and SI show similar coefficients with previous results, confirming the robustness of our conclusion.

TABLE 10.

Robust check: Cumulative profits growth rate of industrial firms

Variables	(1)	(2)	(3)	(4)
	Profits	Profits	Profits	Profits
GRI	0.882***
	(9.817)
CHI		0.832***
		(9.923)
ESI			0.970***
			(7.141)
SI				0.799***
				(8.683)
Capital	1.708***	1.665***	2.028***	1.773***
	(7.728)	(7.596)	(8.222)	(7.882)
PPI	0.960**	0.814*	2.488***	1.140**
	(2.125)	(1.776)	(6.215)	(2.545)
Constant	−103.287**	−88.400*	−247.461***	−116.958***
	(−2.286)	(−1.929)	(−6.017)	(−2.598)
Observations	1011	1011	1011	1011
Adjusted R‐squared	0.255	0.254	0.241	0.242
Month FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
F	78.59	79.84	56.05	65.51

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

In Table 11, we take 6 months lead for the IGDP to examine a longer effect government intervention. GRI, CHI, ESI, and SI show significantly positive coefficients, in line with previous results. These results confirm the stimulating effect of government intervention on economic recovery.

TABLE 11.

Robust check: Six months lead of IGDP

Variables	(1)	(2)	(3)	(4)
	IGDP	IGDP	IGDP	IGDP
GRI	0.174***
	(15.711)
CHI		0.166***
		(15.620)
ESI			0.180***
			(13.842)
SI				0.166***
				(14.445)
Capital	0.135***	0.126***	0.196***	0.149***
	(4.911)	(4.597)	(6.941)	(5.391)
PPI	−0.164***	−0.193***	0.106***	−0.134***
	(−5.129)	(−5.901)	(3.386)	(−4.167)
Constant	16.750***	19.647***	−8.466***	14.312***
	(5.233)	(6.035)	(−2.589)	(4.419)
Observations	961	961	961	961
Adjusted R‐squared	0.241	0.240	0.175	0.208
Month FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
F	109.6	108.4	83.96	91.96

Note: Heteroskedasticity‐robust t‐statistics are reported in parentheses.

***p < 0.01, **p < 0.05, *p < 0.1.

5. CONCLUSIONS AND DISCUSSION

We analyze the impact of government intervention on economic growth. Our results indicate that government intervention could promote economy recovery. Moreover, the stimulating effect of government intervention is more pronounced in the provinces with more diagnosed cases, and higher marketization index and fiscal power.

Our results verify that government intervention has played a crucial role in the economic recovery during the COVID‐19 pandemic. The market is not always efficient, especially in this special period. When the market is unable to adjust the economy, the government should issue appropriate interventions in the economy to keep it stable. In addition, government intervention still depends on government fiscal capacity, regional marketization, and pandemic impact. Therefore, due to heterogeneous local pandemic conditions and economic fundamentals, different governments should make appropriate policies based on the regions' specific conditions.

The COVID‐19 pandemic is one of the great problems which the present world, is faced with, and is detrimental to all countries' economic regardless of their political systems and levels of economic development (Ludvigson et al., 2020). The national governments have already responded with a variety of pandemic‐control measures and fiscal countermeasures, many international cities gradually control the pandemic, and focuses on restarting the economy. Remarkably, China implements appropriate government intervention, and China's return to growth has been stronger than expected. Our study verifies that government intervention has played a critical role in the economic recovery during the COVID‐19 pandemic, and the effect depends on government fiscal capacity, regional marketization, and pandemic impact. Thus, faced with the challenge of the pandemic, governments and policy makers should actively propose public policies and should adjust their policies in the light of specific conditions.

Our study has two limitations that may be addressed in future research. First, this study focuses on the Chinese context, so it should be very cautious to generalize our conclusions to other contexts. Even though regardless of countries' political systems and levels of economic development, the COVID‐19 pandemic is detrimental to all countries' economic (Ludvigson et al., 2020), and to forestall the negative effects. Governmental intervention policies have been widely utilized in most countries, such as US, UK, and the European Union countries. Yet it is worth noting that, the effect of government intervention still depends on pandemic conditions and economic fundamentals, such as government fiscal capacity, regional marketization, and pandemic impact. Thus, our paper verifies that government intervention has played a crucial role in the economic recovery during the COVID‐19 pandemic, and the regulatory approach being taken in Chinese provides an available model for other countries. But at the same time, because of the heterogeneous economic fundamentals, formal institutions and culture, governments and policy makers should adjust their policies in the light of specific conditions when propose public policies. Second, our paper focuses on economic growth (the industrial gross domestic productivity growth rate/the industrial firms' sales growth rate), which is a specific dimension of economic. And it remains unknown about whether the government intervention, both direct and indirect policies, can play a crucial role in other economic dimensions (e.g., economic structure, sustainable economic growth, quality of economic development).

CONFLICT OF INTEREST

No potential conflict of interest was reported by the authors.

SUBMISSION DECLARATION

Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis or as an electronic preprint).

Jiang, D. , Li, W. , Yu, J. , & Zhang, Y. (2022). Do governmental policy interventions help urban economic recovery? Experimental evidence from China's provinces governance amid the COVID‐19 pandemic. Growth and Change, 1–22. 10.1111/grow.12661

DATA AVAILABILITY STATEMENT

The data on government policy and Strength that support the findings of this study are available on request from the corresponding author upon reasonable request. The data are not publicly available due to privacy or ethical restrictions. The data on Capital, PPI, IGDP, Fiscal Income that support the findings of this study are openly available in the China National Statistics Bureau at https://data.stats.gov.cn. The data on Cases and Inflow that support the findings of this study are openly available in Chinese Stock Market and Accounting Research database (CSMAR) at https://cn.gtadata.com/%23/index. The authors confirm that the data on Marketization supporting the findings of this study are available within the article “Marketization index of China's provinces: Neri report 2018” and its supplementary materials.