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Influence of heterogeneity of local officials on the economy of resource-based cities developed with high quality

Publicado en línea: 12 Dec 2022
Volumen & Edición: AHEAD OF PRINT
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Recibido: 22 Apr 2022
Aceptado: 19 Nov 2022
Detalles de la revista
License
Formato
Revista
eISSN
2444-8656
Primera edición
01 Jan 2016
Calendario de la edición
2 veces al año
Idiomas
Inglés
Introduction

A city that develops an industrial economy by utilising existing natural resources is called a resource-dependent city. The emergence of this type of city can speed up the overall industrialisation of the country. Due to the non-renewable nature of natural resources, as a result, economic development is slowed down and even lags behind that of other cities. Therefore, we must pay attention to promoting the sustainable economic development of these cities. China’s development direction has improved the quality of economic development. Cities developed with natural resources need to accelerate their transformation and achieve high-quality economic development rapidly [1]. About 40% of China’s cities depend on exploiting natural resources for their economic growth. Improving the quality of economic development of towns based on the exploitation of resources can improve the progress and quality of China’s economic growth at the present stage [2].

Many scholars at home and abroad have studied the heterogeneity of officials and the speed of regional economic development. Official heterogeneity refers to age, tenure, education level and promotion type; officials with different personal characteristics will make additional financial decisions which will affect the regional economic development. Government behaviour has an impact on the economy of resource-based cities developed with high quality, and local officials are specific implementers of government actions; internal heterogeneity of local officials will act on government behaviour; government decisions can have a substantial impact on local economic development [3]. Therefore, using the panel data of 111 prefecture-level cities that rely on the exploitation of natural resources, this paper makes an empirical study on the heterogeneity of local officials and the economy of resource-based cities developed with high quality to provide a specific reference basis for improving China’s official governance mechanism and promoting the sound and rapid development of urban economy relying on natural resources.

Literature review and study hypothesis
The age of local officials and the economy of resource-based cities developed with high quality

China limits the retirement age of officials; officials close to the retirement age have little interest in the promotion and prefer to reduce the economic objectives of their place of office, which may slow down the speed of local economic development and affect regional economic development [4]. When the age of officials was significantly lower than value of the ‘retirement red line’, the economic output of the area in which they served would increase dramatically, while if they were older, the opposite was true. Age was a key factor affecting the promotion of officials; with the increase in age, the competition among officials became more intense [5]. Generally speaking, the younger the period, the greater the promotion space; the closer the age was to the ‘retirement red line’, the smaller the promotion space was [6]. There was a promotion window period for local officials, and the promotion window period for prefecture-level city officials was generally between 40 years and 50 years; officials in the promotion window would be more motivated to promote regional economic growth to sustain the performance during their tenure. Officeholders often decide how hard they work according to their career development prospects; the officials with better development prospects would have a better effect on promoting the regional economy. To sum up, this study makes Hypothesis 1.

H1: The age of local officials was negatively related to the high-quality development of the urban economy.

Tenure of local officials and the economy of resource-based cities developed with high quality

Chinese local officials have been in the same position for no >5 years, but the actual situation is that most officials with a term of fewer than 5 years will transfer. Since the time of special assessment is not fixed, officials will work hard after taking office to obtain the political achievements on their return. The length of an official’s tenure would affect their government behaviour and economic decision-making. With time, the marginal effect of term increases first and then decreases [7]. Under the system of indefinite tenure, officials would continue to achieve good government performance since taking office to obtain promotion opportunities [8]. Officials would transfer during their period of office, which reflected the flexibility of the term of office; once they took office, officials would start to work hard to obtain the political achievements of the area they served in a short time [9]. Under a fixed period of office, officials would decide their plans during their term of office according to the time of office arrangement. Generally speaking, only near retirement wound officials work hard and make achieve some. See whether they would promote according to the assessment results, and then decide their future employment plan. If the term of office was not fixed, officials did not know when they would be promoted and would always work hard. When civil servants just took office, they will vigorously develop the economy and hope to promote the high-quality development of the local economy. The promotion mechanism based on financial performance appraisal would fully mobilise the enthusiasm of officials to develop the economy to inspect by superior leaders at any time and seize the promotion opportunity. Moreover, the economic return was easy to observe; vigorously developing the economy at the beginning of their tenure of office would help to improve their promotion probability [10]. To sum up, this study makes Hypothesis 2.

H2: When they first took office, the tenure of local officials was positively related to the economy of resource-based cities developed with high quality.

The higher education level of local officials and the economy of resource-based cities developed with high quality

The central government had put forward the policy of making cadres knowledgeable, and the level of education also had a significant impact on the assessment of officials; it had an effect on the development of the local economy; highly educated officials would fully reflect their strength and had certain advantages in the ‘promotion championship’ [11]. Democracies tend to choose highly educated leaders, and civil servants with higher education are more inclined to promote economic change [12]. Civil servants with higher education can have a comprehensive grasp of the local development so that they can better promote the all-round development of the locals. Officials who had received higher education had a better knowledge system, had a higher level of governance ability and could promote local comprehensive and balanced progress. According to the theory of ‘learning by doing’, officials with higher education had better learning ability [13]. As Maslow put it, ‘after meeting basic needs, people will want to realise their value’. Therefore, the basic needs of officials with higher education have been met. They hope to serve local residents during their term of office so that they will work harder. To sum up, this study makes Hypothesis 3.

H3: Local officials with higher education were positively related to the economy of resource-based cities developed with high quality.

Promotion types of local government civil servants and the economy of resource-based cities developed with high quality

The cadre selection system has always focussed on research at home and abroad. China’s individual performance evaluation makes local government civil servants greatly important to economic development. Local economic development would increase the possibility of official promotion [14]. Therefore, under the promotion incentive, local officials would respond positively and promote regional economic growth [15]. The promotion of officials during their term of office would significantly promote the development of the local economy [16]. There are two types of promotion: local promotion and remote transfer. Civil servants promoted locally have more work experience than those transferred from abroad and have a sufficient understanding of local economic conditions and residents’ needs; work can carry out immediately after taking office. However, officials assigned from other places need a period, time to investigate and understand the local area and cannot enter the working state as soon as possible. Newly appointed officials with local work experience can further promote local economic development; compared with the Secretary of the Municipal Party Committee transferred from other places, the political uncertainty of local promoted officials is lower [17]. Officials transferred from other places may implement policies different from those of former officials, resulting in more significant political uncertainty [18]. To sum up, this study makes Hypothesis 4.

H4: Local promotion of government officeholders can promote the quality of local economic development more than those transferred from other regions.

Data source and variable definition
Data source

This paper drew samples from the resource-based cities in China that rely on natural resources to develop the economy from 2013 to 2020, officially released by the State Council; there are 262 areas developed by natural resources, including cities, districts, counties and municipal districts (development zones and management zones). Because the sample data of this study are from prefecture-level cities, they are relatively complete and easy to obtain. Therefore, this study selected 111 cities developed due to local exploitation of natural resources from 2010 to 2019. The specific cities are shown in Table 1. China has been under the ‘administrative contract awarding system’ for a long time; the ‘unitary system’ has been widely used in actual leadership decision-making. Local party committees have more centralised power. The Mayor’s decision-making will also be influenced by the ‘brand’ of the Municipal Party Secretary. In China, the City Party Secretary is more likely to be the number one. This paper defined local officials as the Secretary of the Municipal Party Committee. The resumes of local officials were from People’s Daily Online, the Local leadership database, China economic network local party and government leaders database, and the City selection network. The resumes of some municipal Party secretaries obtained through Baidu Encyclopaedia. Other data were from the Economic Yearbook and the statistical bulletin of national economic and social development over the years; the missing data were estimated by the interpolation method.

Input, output factor and specific definitions of GTFP

Input elementsLabour inputEmployed population
Output elementsCapital investmentInvestment in fixed assets
Energy inputTotal electricity consumption
Expected outputtotal output value (GDP)
Unexpected outputIndustrial wastewater discharge, industrial (smoke) dust discharge and industrial sulphur dioxide discharge

GTFP, green total factor productivity.

Explained variable

China’s development speed accelerated by the emergence of these cities that exploit natural resources, but the consumption of resources and energy was enormous; while vigorously developing the economy, the problem of environmental pollution had gradually emerged. Therefore, cities that exploit natural resources should implement the idea of green transformation. Many scholars at home and abroad for the heterogeneity of local officials and the relationship between the economic development, most of the selected total factor productivity on behalf of the regional economic development in high quality, but the total factor productivity did not take into account to the problem of environmental pollution and resource consumption, and the development of resource-based cities was dependent on the exploitation of natural resources, which often led to the destruction of the environment. Therefore, in the measure of economic development of city resources, increase environmental elements selected for green total factor productivity (lnGTFP) could be more comprehensive, and development level, amount of industrial waste water, industrial dust emissions and industrial SO2 emissions (smoke) were indicators of undesired output, combined with labour input, capital input, energy input and expected output indicators; it could more accurately reflect the high-quality economic development of resource-based cities. Refer to Table 1 for details:

Data envelopment analysis (DEA) was a linear programming model. It was proposed by A. Charnes and W. W. Cooper in 1978 and expressed as an input-output ratio. Under the condition of keeping the input or output of the decision-making unit unchanged, the degree of deviation of the decision-making unit from the production boundary was compared, and the effectiveness of the decision-making unit in the system was evaluated. The SBM model introduced unexpected input index based on the DEA model, which was made up for the deviation or inaccuracy of DEA model calculation. It was a standard method to analyse unexpected output; the specific elements are showed in Table 2. For n decision-making units, m inputs X in each decision-making unit, the expected output of S1 is yg and the expected output of S2 is yb. The specific equations were as follows: ρ=min11mi1mSiX i 01+1 S 1+ S 2 ( r=1 S1 Srg yr0g + r=1 S2 Srb yr0b )\begin{align}{\rho{}}^{*}=\min\frac{1-\frac{1}{m}\sum_{i-1}^m\frac{S_i^-}{X_{i0}}}{1+\frac{1}{S_1+S_2\left(\sum_{r=1}^{S_1}\frac{S_r^g}{y_{r0}^g}+\sum_{r=1}^{S_2}\frac{S_r^b}{y_{r0}^b}\right)}}\end{align} s.t{ y 0 r= Y gλ S g y 0 b= Y bλ+ S b S 0, S g0 S b0,λ0}\begin{align}\text{s.t}\left\{\begin{matrix}y_0^{r}=Y^g\lambda{}-S^g\\y_0^{b}=Y^{b}\lambda{}+S^{b} \\S^-\geq{}0,S^g\geq{}0 \\S^b\geq{}0,\lambda{}\geq{}0\end{matrix}\right\}\end{align}

Main variables and specific declarations

Variable typeVariable nameVariable symbolVariable description
Explained variableHigh-quality economic developmentlnGTFPThe logarithm of GTFP
Explanatory variableAgeAgeAge of Municipal Party Secretary
 Tenure of officeTenTime from taking office to leaving office. The term of office of an official who took office in the first half of the year starts from that year. The term of office of civil servants who took office in the last 6 months calculated from the next month. If a civil servant left office in the first 6 months of the year, his term of office ended in the previous year; If a civil servant left office in the last 6 months of the year, the end time of his term of office would confirm as the current year.
 Education levelEduMaster’s degree or above is record as 1, and the following is record as 0
 Promotion typeProCivil servants transferred from abroad were recorded as 2, the local promotion was recorded as 1 and other circumstances were recorded as 0 (other cases include retirement after leaving office, violation of discipline, etc.)
Control variablesPopulation sizelnpopThe logarithm of resident population
 Government scaleGovGovernment expenditure/GDP
 Education levelEdu2Number of college students/total local population
 Saving rateSaveTotal local deposits/GDP
 Environmental pollution degreePollIndustrial emissions/GDP

GTFP, green total factor productivity.

S was the input factor, Sg was the expected output, Sb was the relaxation variable of the unexpected work and the objective function ρ* decreased to S, Sg and Sb. MATLAB software was used to calculate the data and obtain GTFP.

Explanatory variables

The heterogeneity index of local officials was selected as explanatory variable. The age, tenure, education level and promotion type of officials were essential indicators of the heterogeneity of local officials, and it could affect the economic development of cities exploiting natural resources.

Age (Age): select the age of the municipal party secretary of the sample in that year. The age of local officials when they took office would affect their political behaviours. Whose age was close to the ‘retirement red line’ tended to make conservative political decisions, while officials in the promotion stage would vigorously develop the economy during their tenure in order to obtain promotion opportunities. Therefore, the age of officials was an important factor that affected the government behaviour of resource-based cities and then affected the high-quality economic development.

Tenure of office (Ten): China implemented a limited tenure system, in which the tenure of officials in the same position was generally not >5 years. The key to promotion was political performance and superior evaluation. Officials eager for promotion would quickly promote local economic development after taking office to achieve the purpose of promotion. Therefore, officials in the early stage of their tenure would have an important impact on the high-quality economic development of resource-based cities. It took a specific time for an official to take office or leave office. The term of office of an official who took office in the first half of the year starts from that year. The term of office of civil servants who took office in the last 6 months was calculated from the next month. If a civil servant left office in the first 6 months of the year, his term of office ended in the previous year. If a civil servant left office in the last 6 months of the year, the end time of his term of office would confirm as the current year.

Education level (Edu): one of the important indicators for the selection of cadres in China was the official’s educational background. Officials who had received higher education had strong learning ability and working ability and understood the requirements of their superiors thoroughly; this facilitated the government to make positive decisions, thus affecting the local economic development. In this paper, officials with master’s degree or above were defined as those who had received higher education. Master’s degree or above is assigned as 1, and the following is assigned as 0.

Promotion type (Pro): the promotion of local officials in China included two types: local promotion and transfer to other places. No matter which promotion method, it had an incentive effect on officials and promoted their efforts to achieve political achievements, and different types of official promotion also had an impact on the local economic development. Therefore, in consideration of the relationship between the promotion types of officials and the high-quality economic development of resource-based cities, this paper marked the former Municipal Party Secretary who was transferred from other places as ‘2,’ local promotion as ‘1’ and the other cases as ‘0,’ including retirement after leaving office, violation of discipline, etc.

Control variables

Population size (lnpop): population scale was closely related to the high-quality development of the local economy. The regional population scale reflected the economic consumption level and production scale of the region, as well as the governance of the local government. The more people there were, the higher the GDP would be, which increased the local population. On the other hand, population size also reflected the development potential of a city. The increase of population brought about the aggregation of various industries, which improved the local economic development accordingly. Therefore, the logarithmic measurement of local resident population was selected as a control variable to observe the impact of the heterogeneity of officials in resource-based cities on high-quality economic development.

Government scale (Gov): to some extent, the size of the government reflected the size and development of the region, the government undertook the important task of city development, the larger the size of government, the greater the responsibility shouldered by the region development and the government behaviours and policies decided the direction and quality of economic development; considering the size of government’s influence on the quality and economic development, the selection of government scale was considered as control variables. The government scale wa expressed by expenditure divided by GDP in the government budget.

Education level (Edu2): there was a close relationship between local residents’ education level and local economic development. The level of education was related to the residents’ moral quality and knowledge reserve, which affected the economic development speed of the whole city. Therefore, the ratio of the number of students in regular institutions of higher learning to the local population was selected as the control variable.

Saving rate (Save): the saving rate of residents reflected the living standard of residents to a certain extent. The savings rate could represent the degree to which residents’ basic living needs were met and also reflected the level of regional economic development and people’s well-being. The development of resource-based cities was to promote the overall development of the country and improved the living standards of residents. Therefore, the ratio of local residents’ total savings to regional GDP was selected to represent the control variable.

Environmental pollution degree (Poll): resource-based cities developed their economy by exploiting natural resources. In order to make the city develop sustainable, the impact of resource consumption on the environment could not be ignored. The degree of environmental pollution could not only reflect the local environmental quality but also objectively reflect the economic development due to the exploitation of natural resources. In this paper, the ecological pollution degree was the industrial exhaust emissions divided by local GDP. Refer to Table 2 for details.

Model construction

This paper constructed four models based on research assumptions. Eq. (3) validation H1: The age of local officials negatively related to the high-quality development of the urban economy. Eq. (4) confirmation H2: At the beginning of his tenure, the tenure of local officials was positively related to the economy of resource-based cities developed with high quality. Eq. (5) validation H3: The level of higher education of local officials was positively associated with the economy of resource-based cities developed with high quality. Eq. (6) validation H4: Compared with the officials transferred from other places, the promotion of local officials could improve the quality of regional economic development more than those transferred from other regions. The specific models were as follows: lnGTFPi,t=α0+α1Agei,t+α2ctrlsi,t+εi,t\begin{align}\text{lnGTFP}_{i,t}={\alpha{}}_0+{\alpha{}}_{1}\text{Age}_{i,t}+{\alpha{}}_2{ctrls}_{i,t}+{\varepsilon{}}_{i,t}\end{align} lnGTFPi,t=α0+α1Agei,t+α2ctrlsi,t+εi,t\begin{align}\text{lnGTFP}_{i,t}={\alpha{}}_0+{\alpha{}}_{1}\text{Age}_{i,t}+{\alpha{}}_2{ctrls}_{i,t}+{\varepsilon{}}_{i,t}\end{align} lnGTFPi,t=α6+α7Edui,t+α8ctrlsi,t+εi,t\begin{align}\text{lnGTFP}_{i,t}={\alpha{}}_6+{\alpha{}}_{7}\text{Edu}_{i,t}+{\alpha{}}_8{ctrls}_{i,t}+{\varepsilon{}}_{i,t}\end{align} lnGTFPi,t=α9+α10Proi,t+α11ctrlsi,t+εi,t\begin{align}\text{lnGTFP}_{i,t}={\alpha{}}_9+{\alpha{}}_{10}\text{Pro}_{i,t}+{\alpha{}}_{11}{ctrls}_{i,t}+{\varepsilon{}}_{i,t}\end{align}

Eqs (3)–(6) described the relationship between official heterogeneity and urban economic growth, lnGTFP represented the economic development level, Age represented local officeholders’ age, Edu represented the education level of local officials, Tenure represented the tenure of local officials, Pro represented the promotion type of local officials, Ctrls represented the population size (lnpop), government size (Gov), an education level (Edu2), savings rate (Save) for the control variables including the degree of environmental pollution (Poll), I represented the I sample, t defined the year and ε represented the random error term.

Analysis of empirical results
Analysis results of descriptive statistics

Table 3 shows the results of descriptive statistics:

Analysis results of descriptive statistics

Variable nameSampleAverage valueStandard deviationMinimumMaximum
lnGTFP1,1104.292.890.0310
Year1,11020142.8720102019
Age1,11053.463.364160
Ten1,1103.671.618
Edu1,1100.840.3701
Pro1,1100.890.6902
lnpop1,1105.580.683.346.97
Gov1,11021.5810.721.6980.93
Edu21,1101.141.130.0215.82
Save1,1108.044.44095.65
Poll1,1104.645.410.0163.43

GTFP, green total factor productivity.

As it could be seen from the descriptive statistical results in Table 3, the high-quality economic development (lnGTFP) was 4.29, the maximum value was 10 and the minimum value was 0.03; regional resource utilisation rate was out of line with economic growth. From the characteristics of officials, the average age (Age) of officials was 53.46 years, the maximum value was 60 and the minimum value was 41; it showed that the age span of officials in the sample cities was significant. The average tenure (Ten) of office of officials in resource-based cities was 3.67 years, which did not reach the specified 5-year term; it showed that resource-based prefecture-level city officials were transferred; the minimum length of service of civil servants was 1 year, and the maximum length of service was 8 years. The average education level of officials (Edu) was 0.84, which indicated that most officials had received higher education. China had certain restrictions on the education level of officials in cadre selection, which was related to the cadre selection mechanism. The average promotion type of officials (Pro) was 0.89; the results show that the replacement of local civil servants was local primarily promotion.

From the perspective of control variables, the average value of population size (lnpop) was 5.58, the minimum value was 3.34 and the maximum value was 6.97, indicating that resource-based cities were densely populated, and the use of resources to develop economy required a large number of labour force, thus increasing many jobs and attracting local and foreign personnel.

The average value of government size (Gov) was 21.58, the minimum value was 1.69 and the maximum value was 80.93, indicating that the government expenditure of different resource-based cities varies greatly in terms of local GDP. Government financial expenditure also fluctuated with regional development, which was related to the development of different local resource economies.

The average value of educational level (Edu2) was 1.14, the minimum value was 0.02 and the maximum value was 15.82. The educational level of different resource-based cities varies greatly. From the average value, the overall educational level of residents in resource-based cities was not high, indicating that educational development might be neglected in the process of resource economy development.

For savings rate (Save) with a mean of 8.04, the minimum value was 0 and the maximum value was 95.65 because a part of the city’s savings rate was too small; so, descriptive statistics results showed that the minimum value was 0; the results in Table 3 showed that in different parts, the saving rate difference was very big, and in resource-based cities in the economic development after the improvement of residents savings rate, it was lower than average and not obvious.

For environmental pollution (Poll) with a mean of 4.64, the minimum value was 0.01 and the maximum value was 63.43. Although resource-based cities exploited different natural resources for economic development, they all caused damage to the environment to a certain extent. The average level of environmental pollution in resource-based cities was small, indicating that the government and enterprises paid attention to environmental protection while developing economy.

Relevance analysis

Table 4 shows the results of the correlation analysis.

Relevance analysis

VariablelnGTFPAgeTenEduPro
lnGTFP1    
Age−0.0131   
Ten0.0340.0201  
Edu0.021−0.197***−0.0241 
Pro0.0180.050*0.099***0.0011
lnpop0.126***0.208***0.0230.066**0.092****
Gov−0.114***−0.0420.112***−0.000−0.052*
Edu2−0.0110.045−0.056*−0.077**−0.068**
Save−0.085***0.061**0.0090.017−0.053*
Poll−0.219***−0.166***0.0440.056*0.005
VariablelnpopGovEdu2SavePoll
Age     
Ten     
Edu     
Pro     
lnpop1    
Gov−0.112***1   
Edu2−0.181***−0.256***1  
Save−0.0400.524***0.0081 
Poll−0.231***−0.023−0.016−0.104***1

***Meant p < 0.01.

**Meant p < 0.05.

*Meant p < 0.1.

GTFP, green total factor productivity.

Table 4 shows that there was a negative correlation between the age (Age) of local officials and high-quality economic development (lnGTFP); it showed that local officials close to retirement were not promoting the economy of resource-based cities developed with high quality, which was consistent with H1. The length of service of civil servants (Ten) is positively related to the economy of resource-based cities developed with high quality (lnGTFP); it was consistent with the content of Hypothesis H2. When civil servants first took office, officials had high enthusiasm to develop the local economy. The study regarded the academic qualifications of civil servants (Edu) as positively related to the economy of resource-based cities development with high quality (lnGTFP); this conclusion proved that H3 was right; this result shows that civil servants with higher education can improve the local economy. There was a frontal correlation between the promotion type of official (Pro) and high-quality economic development (lnGTFP). Local promoted officials could actively promote high-quality local economic growth, which confirmed H4.

Regression analysis

Models 3–6 were used to conduct regression analysis on the data of sample cities from 2010 to 2019. Table 5 showed the results.

Regression analysis results

VariablelnGTFPlnGTFPlnGTFPlnGTFP
Age−0.055**   
 (–2.13)   
Ten 0.09*  
  (1.80)  
Edu  0.228 
   (1.00) 
Pro   0.015
    (0.13)
lnpop0.307**0.307**0.307**0.253*
 (2.31)(2.31)(2.31)(1.93)
Gov−0.024***−0.024***−0.024***−0.024***
 (–2.71)(–2.71)(–2.71)(–2.62)
Edu2−0.043−0.043−0.043−0.054
 (–0.55)(–0.55)(–0.55)(–0.69)
Save−0.040*−0.040*−0.040*−0.043**
 (–1.90)(–1.90)(–1.90)(–2.04)
Poll−0.119***−0.119***−0.119***−0.115***
 (–7.35)(–7.35)(–7.35)(–7.14)
r2_a0.06950.06840.06650.0656
F14.8014.5614.1613.99

***Meant p < 0.01.

**Meant p < 0.05.

*Meant p < 0.1.

GTFP, green total factor productivity.

According to the results of empirical analysis in the first column of Table 5, the F value in Eq. (3) was 14.80, and the adjusted R2 was 0.0695. The regression coefficient between the age of local officials (Age)and high-quality economic development (lnGTFP) was negative and negatively correlated, which verified H1. The younger the officials were, the more room they would have for promotion. They would strive to improve their performance during their term of office, pass the assessment of their superior leaders and finally achieve the purpose of advertising; for officials whose age was close to the ‘retirement red line,’ it was on the contrary.

According to the results in the second column of Table 5, the F value in Eq. (4) was 14.56 and the adjusted R2 was 0.0684. The regression coefficient between the term of office of local officials (Ten) and high-quality economic development (lnGTFP) was positive and positively correlated, which verified the H2. The uncertain tenure system arrangement made officials unable to accurately predict the time node of special review; so, officials could only think that assessment was ubiquitous. Under this expectation, the longer the term of office, the greater the promotion pressure. If officials wanted to promote, they would make continuous efforts from the time they took office to improve the government performance during their tenure and boost the economy of resource-based cities with high quality.

According to the results in the third column of Table 5, it could be seen that the F value in Eq. (5) was 14.16, and the adjusted R2 was 0.0665. The regression coefficient between the education level of local officials (Edu) and high-quality economic development (lnGTFP) was positive and positively correlated, which verified H3. Officials with higher education had systematically studied governance methods. Their ability to collect information and make decisions can promote economic growth. Therefore, highly educated officeholders had excellent governance quality and were also keen on developing the local economy, which had extensively promoted the economy of resource-based cities developed with high quality.

In the last column of Table 5, the value of F in Eq. (6) was 13.99, and the adjusted R2 was 0.0656. The promotion type of local civil servants was positively correlated with high-quality economic development. This result verifies that H4 is correct. Civil servants promoted locally have more work experience than those transferred from abroad and have a sufficient understanding of local economic conditions and residents’ needs and could invest in the work of economic development more quickly. Due to different working environments and ideas, officials transferred from other places might make different political decisions from the former officials, which would affect the local economic development.

Conclusions

After analysing the 2010–2019 data of 111 cities in China that rely on resource exploration for development, using the method of empirical research, this paper studies the relationship between the heterogeneity of local civil servants and cities that use natural resources to develop the industry. After analysis, this study drew several conclusions:

There is a negative correlation between the age of local officials and the quality of economic development of cities developed through the rational use of natural resources.

When they first took office, the tenure of local officials is positively related to the economy of resource-based cities developed with high quality.

Local officials with higher education are positively related to the economy of resource-based cities developed with high quality.

Local promotion of government officeholders can promote the quality of local economic development more than those transferred from other regions.

Policy recommendations
Pay attention to the leaving assessment system for senior officials

The competition among officials in the promotion window was very fierce. Due to the existence of promotion incentives, officials were motivated to develop the local economy. Government civil servants who are about to retire will make more conservative political decisions because they have no enthusiasm to promote economic development. Therefore, senior officials should guide to improve their work enthusiasm, and an effective reward and punishment system should be established. Officials who are about to retire should comprehensively assess from the economy, environment and so on.

Implement the system of limited tenure

At present, Chinese officeholders hold the same position for no >5 years. The short term might lead to insufficient time for officials to deeply understand the regional development situation, which was not conducive to implementing reform policies and was prone to short-term behaviour. Therefore, the 5-year tenure system should be implemented by the central government. The implementation of the fixed tenure system can firstly enable officials to work at ease during their tenure, secondly contribute to the stability of government policies and finally improve the quality of economic development of cities exploiting natural resources.

Government civil servants are required to have higher education

The official assessment system should emphasise the policy of ‘revolution, knowledge, and specialisation. ‘Further increase in the proportion of officials’ academic qualifications in the promotion assessment encouraged officials to improve their independent learning ability, strengthen theoretical knowledge learning and improve the governing level of the whole team of officials. Based on their own knowledge, highly educated officials can quickly accept new governing ideas and methods, better improve the efficiency of policy decision-making and help promote local economic reform. At the same time, more attention should be paid to reducing the impact of resource exploitation on the environment so as to realise the high-quality economic development of resource-based cities.

Reasonably arrange promotion methods

Officials transferred from other places did not know enough about the basic situation of the local area and needed a period of adaptation. During this period, the efficiency of regional economic development might reduce. In contrast, local promoted officials were more familiar with local resources and economic development. They had a better understanding of the government’s previous policies so that they could work quickly after taking office. Therefore, the reasonable choice of the promotion mode of local officials would help to continue the economic policy and promote the economy of resource-based cities developed with high quality.

Main variables and specific declarations

Variable type Variable name Variable symbol Variable description
Explained variable High-quality economic development lnGTFP The logarithm of GTFP
Explanatory variable Age Age Age of Municipal Party Secretary
  Tenure of office Ten Time from taking office to leaving office. The term of office of an official who took office in the first half of the year starts from that year. The term of office of civil servants who took office in the last 6 months calculated from the next month. If a civil servant left office in the first 6 months of the year, his term of office ended in the previous year; If a civil servant left office in the last 6 months of the year, the end time of his term of office would confirm as the current year.
  Education level Edu Master’s degree or above is record as 1, and the following is record as 0
  Promotion type Pro Civil servants transferred from abroad were recorded as 2, the local promotion was recorded as 1 and other circumstances were recorded as 0 (other cases include retirement after leaving office, violation of discipline, etc.)
Control variables Population size lnpop The logarithm of resident population
  Government scale Gov Government expenditure/GDP
  Education level Edu2 Number of college students/total local population
  Saving rate Save Total local deposits/GDP
  Environmental pollution degree Poll Industrial emissions/GDP

Relevance analysis

Variable lnGTFP Age Ten Edu Pro
lnGTFP 1        
Age −0.013 1      
Ten 0.034 0.020 1    
Edu 0.021 −0.197*** −0.024 1  
Pro 0.018 0.050* 0.099*** 0.001 1
lnpop 0.126*** 0.208*** 0.023 0.066** 0.092****
Gov −0.114*** −0.042 0.112*** −0.000 −0.052*
Edu2 −0.011 0.045 −0.056* −0.077** −0.068**
Save −0.085*** 0.061** 0.009 0.017 −0.053*
Poll −0.219*** −0.166*** 0.044 0.056* 0.005

Input, output factor and specific definitions of GTFP

Input elements Labour input Employed population
Output elements Capital investment Investment in fixed assets
Energy input Total electricity consumption
Expected output total output value (GDP)
Unexpected output Industrial wastewater discharge, industrial (smoke) dust discharge and industrial sulphur dioxide discharge

Analysis results of descriptive statistics

Variable name Sample Average value Standard deviation Minimum Maximum
lnGTFP 1,110 4.29 2.89 0.03 10
Year 1,110 2014 2.87 2010 2019
Age 1,110 53.46 3.36 41 60
Ten 1,110 3.67 1.6 1 8
Edu 1,110 0.84 0.37 0 1
Pro 1,110 0.89 0.69 0 2
lnpop 1,110 5.58 0.68 3.34 6.97
Gov 1,110 21.58 10.72 1.69 80.93
Edu2 1,110 1.14 1.13 0.02 15.82
Save 1,110 8.04 4.44 0 95.65
Poll 1,110 4.64 5.41 0.01 63.43

Regression analysis results

Variable lnGTFP lnGTFP lnGTFP lnGTFP
Age −0.055**      
  (–2.13)      
Ten   0.09*    
    (1.80)    
Edu     0.228  
      (1.00)  
Pro       0.015
        (0.13)
lnpop 0.307** 0.307** 0.307** 0.253*
  (2.31) (2.31) (2.31) (1.93)
Gov −0.024*** −0.024*** −0.024*** −0.024***
  (–2.71) (–2.71) (–2.71) (–2.62)
Edu2 −0.043 −0.043 −0.043 −0.054
  (–0.55) (–0.55) (–0.55) (–0.69)
Save −0.040* −0.040* −0.040* −0.043**
  (–1.90) (–1.90) (–1.90) (–2.04)
Poll −0.119*** −0.119*** −0.119*** −0.115***
  (–7.35) (–7.35) (–7.35) (–7.14)
r2_a 0.0695 0.0684 0.0665 0.0656
F 14.80 14.56 14.16 13.99

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