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ISSN : 1225-8504(Print)
ISSN : 2287-8165(Online)
Journal of the Korean Society of International Agriculture Vol.30 No.4 pp.269-276
DOI : https://doi.org/10.12719/KSIA.2018.30.4.269

Importance of Governance Infrastructure on Sustainable Agricultural Production: A Case of Central Asia

Rovshen Ishangulyyev, Sang Hyeon Lee†
Department of Agricultural and Resource Economics, Kangwon National University, South Korea
Corresponding author : (Phone) +82-33-250-8664 (E-mail) shl@kangwon.ac.kr
August 10, 2018 October 28, 2018 November 2, 2018

Abstract


Achievement of sustainable agricultural development is one of the most important issues in many developing countries. In addition, basic inputs such as labor and capital, and social and environmental factors are important factors in agricultural production in developing countries. This study examines impact of governance conditions of Central Asian newly independent Post-Soviet Union countries on agricultural production and production efficiencies by using World Bank’s Worldwide Governance Indicators. The studied countries had similar socio-economic conditions and environments before independence; however, those countries have different forms of development. Empirical results showed that governance improvement helped to increase agricultural production significantly. In addition, we found that each governance factor has different effects on agricultural production. The findings of this study would be a base for sustain agricultural production in developing countries, and stressed the necessity of improved governance conditions as well as input investments for achievement of agricultural development.


agricultural production , central asia , governance , governance indicators , cobb-douglass production function

지속가능한 농업생산에 있어서 거버넌스 기반의 중요성: 중앙아시아 사례 분석

Rovshen Ishangulyyev, 이 상현†
강원대학교

초록

    Kangwon National University
    520170184

    Introduction

    In many developing countries improving agricultural production is important issue in economic development (Tayebi, 2014). These issues can be reasoned by lack of physical and human capital, technology improvement that is main driving engine of production (Lio & Liu, 2008). So, government and international investments to agriculture through development assistance programs and improvement of infrastructures are crucial to increase agricultural production.

    Many previous studies have done on the relation with main inputs such as capital, labor, land and other aspects to find ways to improve agricultural production. Shahabinejad & Akbari (2010) studied to find the efficiency of labor, land use and the other inputs for eight developing countries (Bangladesh, Egypt, Indonesia, Iran, Malaysia, Nigeria, Pakistan and Turkey). Kibonge (2013) studied the relation between agricultural productivity rates with institutions and climatic factors in case Sub-Saharan Africa. Niyazmetov et al. (2012) conducted research for Khorezm region of Uzbekistan to examine the relation between agricultural production and machinery usage. Lerman et al. (2003) studied about implementation of land reforms and labor migration for Post-Soviet Union countries case to discuss difficulties in agricultural production after independence. There are several studies on the relationship between agricultural production and inputs but studies on the effect of governance infrastructure on agricultural production are rear.

    Besides productive and social infrastructures, governance condition also has directly and indirectly impacted to the improvement of agricultural production. Hayami & Ruttan (1985) argues that barriers for enhancing agricultural production not only scarcity of natural endowments or undeveloped technological potential from the available resources but also poor institutions that restrict implementation of the innovations and new suitable technologies. Better governance supports the comparative and lower transaction cost environment, which promotes modern innovations and motivates the adaptation of new technologies and organization forms (Lio & Liu, 2008).

    Thus, we conducted this study to examine the impacts of governance infrastructure on agricultural production in countries of Central Asia. The subject area of this study is Central Asia which consists of five independent countries: Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan. All these countries got independence from Union of Soviet Socialist Republics (USSR) in 1991. Prior to independence of all Soviet-Union States were socio-economically interdependent within the central planned Soviet economy (Hamidov et al., 2016). After independence all Central Asian countries began their own development path according to political, social, natural, and geographical condition. Turkmenistan and Kazakhstan have joined the upper middle-income group, while other three countries remain in the lower-middle income group (Batsaikhan & Dabrowski, 2017). So, corresponding to above mentioned arguments it is reasonable to examine the impact of the governance on agricultural production, especially for Central Asia. Additionally, there is no study which examines impact of governance on agriculture production only focused to Central Asia.

    The remain part of paper organized as follows: “Theoretical framework” (Section 2) introduces the theoretical relationship of governance infrastructure and agricultural performance is discussed. “Model and Data” (Section 3) describes the methodology and dataset, variable definitions. “Estimation and results” (Section 4) presents the empirical results. “Conclusions” (Section 5) concludes the paper.

    Theoretical Framework

    In this section theoretical relationship of governance infrastructure and agricultural performance was discussed. In beginning we started by investigating different aspects of governance and the various causal factors that can affect to agricultural performance. Following Kaufmann et al. (2010), statues of governance infrastructure can be expressed with Worldwide Governance Indicators (WGI). WGI consists of six indicators, and each indicator shows different aspects of governance infrastructure. The list of indicators are as follows: (a) Control of corruption (COC), (b) Rule of law (ROL), (c) Government effectiveness (GOVEFF), (d) Regulatory quality (REGQ), (e) Political stability and absence of violence/ terrorism (POLSTAB), and (f) Voice and accountability (VAA).

    “Control of corruption” means the rate to which public power had implemented for private gain, including grand and petty form of corruption (Kaufmann et al., 2010). The existence of corruption is often a demonstration of an absence of respect on the both the corrupted and corrupter for the rules that managing their interactions (Kaufmann et al., 2010). Since majority of Central Asian countries are in transition and developing period so that the governments are closely engaged in supply of inputs, production and marketing. Such government intervention increases the possibility of corruption in rent-seeking activities (Fink, 2002). For example, individuals who have close relationships with the government can amend the rules on their benefits and it might result in negative effects on efficiency. In weak control of corruption situation, producers will focus on rent-seeking activities rather than production. Reducing corruption that destroys the governance infrastructure is important for agricultural development (North, 1987).

    “Rule of law” shows the power to which institutions have confidence in and keeps the rules of society (Kaufmann et al., 2010). In particularly, it is related to reliability to the courts and the police, and the quality of contract enforcement, as well as likelihood of violence and crime. A society that is good in respect, enhances an environment in predictable and introduces fair rules from the basis of social and economic interactions. In this kind of society, violent crime are low, the judiciary tries to predictable and effective, and the trust in the contract enforcement is high (Kaufmann et al., 2010). Living example can be a Syrian case; around half of total agricultural production has lost just because of absence of laws (Tull, 2017). If there are no government, no law and no enforcement then it will lead to production loss. Individuals in this kind of society would lose incentives to produce instead prefer seek easy way to live. If the protection of enforcement of contracts and protection property are lacking, then it is reasonable to have scarcity of private investment on agricultural activities. For example, a secure property right to land is needed to make people confident in making the investment which will lead to increase production. Since 2000, Uzbekistan implemented long time secure ownership rights for Dekhan farmers’ which is free from government intervention in production and marketing that had leaded to remarkable increase in agricultural production (Djalalov & Gemma, 2006).

    “Government effectiveness” means government ability to create and implement better policies and providing good infrastructure (Kaufmann et al., 2010). Fan et al. (2004) emphasized that sustainability and development of agriculture depend on social infrastructure and other important institutions. After independence, Tajikistan tried to implement many reforms to enhance economic development, but implementation of reforms was slow and still the country is suffering from unemployment, lacking of job opportunities, and low investments (Mukhamedova & Wegerich, 2018). In addition, good government is more likely to provide beneficial macroeconomic policies to agricultural production, such as prudent fiscal policies, positive interest rate and good exchange rates that are significant to create an environment that is conducive to wide-spread agricultural development (Tomich et al., 2018).

    “Regulatory quality” that indicates the government tendency to accept market-friendly policies. These policies include control of price and excessive regulation of many areas, such as business development and foreign trade (Kaufmann et al., 2010). Poor regulatory quality affected by industrial protectionism which is domestic trade policies that can cause to the balance between domestic and world prices and denying access to international markets. These kinds of governments incline to involve in industrial protectionism and adopt policies that levy indirect taxes on agriculture (Lio & Liu, 2008). Since 1996 Kyrgyzstan had begun implement market based reforms. Market based reforms included market liberalization and land privatization thus strongly recovered agricultural production (Broka et al., 2016). Among Post-Soviet Union countries, Kyrgyzstan is one the fastest economy that has successes in transition to market economy (Batsaikhan & Dabrowski, 2017).

    “Political stability” is related to the perception of the likelihood that the government in power will be overthrown or destabilized by violent and/or unconstitutional means (Kaufmann et al., 2010). Mostly overthrowing or destabilizing the government brings conflicts or civil wars. Furthermore, country where conflict exist, there is food insecure. Syria, Tajikistan and Kyrgyzstan had experienced conflicts or civil wars in different period of time. If we look close to Syria, the conflict has caused to food insecure with several ways: lack of energy supply, shortage of workers, costly production and limited activities increases prices of food, lack of water because of destroyed water supply channels and lack of special equipment (Tull, 2017). Another examples can be expressed Tajikistan’s civil war in 1992-1997 which brought sharp fall in production (Mukhamedova & Wegerich, 2018) and in 2011 Kyrgyzstan’s stagnation in agricultural production by following conflict in 2010 (Broka et al., 2016).

    “Voice and accountability” refers the rate of one country citizen’s participation in government selection, freedom of speech and free media (Kaufmann et al., 2010). Chinese rural local government selection might be good evidence to distinguish the relationship with agricultural production. In ten thousands of Chinese villages since 1980 local government election had held. This election activity significantly improved the share of investment in the total expenditure and enhanced production (Zhang et al., 2004). This indicator is also mattered with the independence of the media that plays a significant role in the controlling those officials in authority and holding them responsible for their actions. In a distribution of such information to citizens and collecting information in creating public policies media plays important role (Olper & Swinnen, 2013).

    According to characteristics of governance indicators following Méon & Weill (2005) we can create three dimensions. The first dimension can be expressed as the “Respect for the institutional framework”, which means the respect of citizens for the governing economic institutions and the social interactions. This dimension is relate to “Control of corruption” and “Rule of law”. The second dimension can be expressed as the “Government action”, which is ability of governance to implement and formulate policies effectively. This dimension is related to “Government effectiveness” and “Regulatory quality”. The third dimension can be explained as the “Selection of authority”, which is engaged in selection, monitor and replacement of the governments. This dimension is related to “Political stability” and “Voice and accountability”.

    The all six World Bank governance indicators – the control of corruption, rule of law, government effectiveness, regulatory quality, political stability, and voice and accountability are recognized by researchers as the effective tools for evaluation the status of governance in various countries. However, it is difficult to separate the effects of an individual indicator because they have a high correlation with each other (Table 1).

    The effectiveness of one indicator depends on the other indicators’ effectiveness; the issue in any one of the indicators will compromise the other indicators’ effectiveness (Azmat & Coghill, 2005). For example, to have government effectiveness in providing public goods and services, there is important to have the political stability. Also a lack of the citizen’s ability to make rational selection of the government and absence of an independent media are more likely to bring the corruption abundance and scarce in accountability. In this case government may implement market-unfriendly policies, as a result, people will lost the confidence in the government and abiding by the rules. So, unable to control corruption or realization of rule of law will lead decreasing government effectiveness and accountability which can some cases destroy the political stability and regulatory framework (Azmat & Coghill, 2005).

    Model and Data

    To analyze the impact of government conditions on agricultural production, we used the Cobb-Douglas production function. The Cobb-Douglass production function has been widely used for agricultural studies (Lio & Hu, 2009). The basic form of the Cobb-Douglas production function is shown in the following equation (1).

    Y = A L β K α
    (1)

    Where Y indicates the total agricultural production, L is labor input, K is capital input, A is total factor productivity. In addition to the basic form of Equation (1), this study considered the size of agricultural land and the ratio of permanent croplands to total land considering the specificity of agriculture and also included the conditions of governance according to the purpose of this study as follow:

    A P = β 0 L β 1 K β 2 A L β 3 L S β 4 G β 5
    (2)

    Where AP indicates the total agricultural production, AL is the agricultural land size, LS is the ratio of permanent croplands to total land, G is the condition of governance. The analysis of this study can be classified into two types: one is to analyze the impact of overall government conditions on agricultural production, and the other is to analyze the relationship between specific government indicators and agricultural production. Based on the production function of equation (2), this study set up an empirical analysis model as equation (3). Because of high correlation between these six indicators, if it will have regressed in same time simultaneously then it will lead to serious multicollinearity problems (Table 1). To avoid these kind multicollinearity problems, all six governance indicators converted to single indicator that expresses the Governance Infrastructure Index (GII) by the calculating mean value and rescaling the mean value ranging within 0 and 1.

    ln AGRTP i , t = β 0 + β 1 ln LABOR i , t + β 2 ln AGRCAP i , t           + β 3 ln LAND i , t + β 4 ln LANDS i , t           + β 5 ln GII i , t + ε i , t
    (3)

    All variables converted to logarithmic form. Where AGRTPi,t indicates the total agricultural production of ith country at time t, AGRCAPi,t is total agricultural capital, LABORi,t is employment in agricultural sector, LANDi,t is used arable land, LANDSi,t is the ratio of permanent croplands to total land, of ith country at time t respectively.

    The six governance indicators separated three dimension according to their characteristics, in order to examine the effect of each dimensions to agricultural production. Each dimension consists of two governance indicators. Explanation of dimensions as below: (a) Respect of institutional framework (RIF) which consists of COC and ROL; (b) Government action (GA) which contains GOVEFF and REGQ; (c) Selection of authority (SA) which consists of VAA and POLSTAB. All dimensions obtained by calculating mean of two governance indicator and rescaled ranging between 0 and 1.

    ln AGRTP i , t = β 0 + β 1 ln RIF i , t + β 2 ln AGRCAP i , t           + β 3 ln LABOR i , t + β 4 ln LANDS i , t           + β 5 ln LANDS i , t + ε i , t
    (4)
    ln AGRTP i , t = β 0 + β 1 ln GA i , t + β 2 ln AGRCAP i , t           + β 3 ln LABOR i , t + β 4 ln LAND i , t           + β 5 ln LANDS i , t + ε i , t
    (5)
    ln AGRTP i , t = β 0 + β 1 ln SA i , t + β 2 ln AGRCAP i , t           + β 3 ln LABOR i , t + β 4 ln LAND i , t           + β 5 ln LANDS i , t + ε i , t
    (6)

    Six governance indicators divided into three dimensions are used in the equations (4), (5), and (6). With those models, the effect of the governance infrastructure can be estimated in three dimensions separately. By using the governance infrastructure indexes that provided by World Bank database and developed by Kaufmann at el., (2010), which show governance infrastructure conditions over the 1996-2017 period.

    Panel data consisting of five countries by balanced twenty-one years (1995~2015) was used in this study. Five countries are Central Asian countries that started to economic development at the same time after getting independence from Union of Soviet Socialist Republics (USSR). Data for six governance infrastructure indicator, aggregate and individual governance indicators were obtained from authorized database sources, such as FAO, World Bank and ILO. Governance indicators consists of six variables which are measurement for the Control of corruption (COC), Government effectiveness (GOVEFF), Political stability and absence of violence/terrorism (POLSTAB), Regulatory quality (REGQ), Rule of law (ROL), Voice and accountability (VAA). These six indicators have measurement range from -2.5 to 2.5, higher value shows better governance.

    Table 2, summarizes definitions and sources of variables. Data for total production of agricultural sector (AGRTP), agricultural capital stock (AGRCAP), and arable land (LAND) were obtained from FAOSTAT(2018). Information about the ratio of permanent croplands to total land (LANDS) was obtained from World Bank’s database (Wiebe, 2003). Latruffe et al. (2004) used this variable as determinant of technical efficiency on crop and livestock production, while Lio & Hu (2009) used the ratio of permanent croplands to total land in efficiency analysis of agricultural production. Table 3, shows statistic for variables.

    Estimation and Results

    The strongly balanced panel database structure consists from 5 countries and 105 observations for 21 years. In order to verify the suitability of the GII variable for use, five different specified models were estimated (Table 4). All variables were converted to logarithmic form. According to Hausman specification test results, we employed Random-Effect model. In the model (a) of Table 4, only three main production inputs were included. We used LANDS as a control variable and included it in the model (c) and the model (d). GII was used in the model (b) and the model (d).

    Given the explanatory power of the model and the significance of the variables, we concluded that the use of the model (d) is justified. Consequently, our estimation results in the model (d) were positive and statistically significant which support our hypothesis that better government infrastructure can enhance agricultural production. Other factors except labor had a significant positive effect on agricultural production. The negative effect of labor on agricultural production appeared due to the agricultural population has decreased during the period but the agricultural production has increased because of technology development. All Central Asian countries experienced labor migration from agricultural sector to other sectors. The labor migration was substituted by capital accumulation and technology improvement. It is the limit of this study that we couldn’t find and use indicators that can reflect technical improvement.

    So far we examined the impact of GII to agricultural production, which indicates the overall governance condition of studied countries. However, by dividing the governance indicators into three dimensions we had been able to analyze which dimension has more impact on agricultural production. Table 5 reports the estimation results of the equation (4), (5) and (6). The parameters of dimension were positive and statistically significant. As well as these results were consistent with the results of Table 4, which means better governance helps to enhance agricultural production for Central Asia. However, the effects on agricultural production differed by dimension. Respect for institutional framework (RIF) has the largest coefficient, followed by Government Action (GA). According to these findings, the order of dimension’s importance to enhance the production following as “Respect for institutional framework”, “Government action” and “Selection of authority”.

    Conclusions

    Sustainable agricultural development is one of the most important challenge for developed and developing countries. Several efforts have been implemented to improve production infrastructure, agricultural technologies and so on to achieve sustainable agricultural development. However, since last decades only, scholars and policy-makers had begun to examine the relation of governance with agricultural performance.

    Using the six aggregated governance indicators from World Bank, we studied whether the differences in the governance infrastructure can explain the heterogeneity in agricultural production among five Central Asian countries, whose economy had been controlled by central plan economy of USSR since 1991. Once after independence, each country implemented their own model/path of development. The results of this study showed that improvement of governance infrastructure can lead to increasing agricultural production, ceteris paribus. The findings of this study are in line with Hayami and Ruttan (1985), who approved that the governance is basic factor interpreting the economic performance of developing countries. We also examined the impacts of governance infrastructure in three different dimensions to agricultural production, and found that all dimensions have positive impact on agricultural production. However, each effect of three dimensions was varied. The results of present study showed that "Respect for institutional framework" has the greatest impact on agricultural production compared to "government action" and "selection of authority". This means that "Respect for institutional framework" is the most important for the governments of Central Asian countries to control of corruption and establish the rule of law in order to optimize agricultural production. Of course, because all the dimensions are significant, improvement of other dimensions are needed to enhance sustainable agricultural production. It would be great and robust, if we analyzed the impacts of government conditions on agricultural production by country wise, and findings could have more implications. However, due to several circumstances, we were not able to analysis those impacts country wise and this is the limitation of this study. Further, country wise impacts assessments are needed to address issues related to governance infrastructure and its impact on the agricultural production for overall agricultural development and boost the national economy.

    적 요

    1. 중앙 아시아는 5 개의 국가로 구성되어 있으며, 이 국가 들은 1991년에 소련 연방에서 독립하였다. 독립 이전에는 5개 국가 모두 공산주의 통치 하에 동일한 소비에트 계획경제 체 제를 가지고 있었다

    2. 1991년 이래로 중앙 아시아 국가들은 정치적, 사회적, 자 연적, 지리적 조건에 따라 각기 다른 개발 경로를 경험하였다.

    3. 더 나은 통치 환경은 현대 기술 혁신을 장려하고 토지에 대한 신기술의 적용 및 토지에 대한 권리를 보장하도록 동기 를 부여한다. 또한 상대적으로 낮은 거래 비용이 조성될 수 있도록 지원하여 생산 증대로 이어질 투자를 촉진한다.

    4. 따라서 통치 환경의 개선은 농업 생산 증대에도 중요한 요인이다. 본 연구는 통치 환경과 농업 생산과의 관계를 실증 적으로 분석하고 이를 검증하였다.

    5. 본 연구의 결과는 농업 생산의 증대를 위하여 통치 환 경의 개선이 중요함을 입증하였으며 , 그 중에서도 부패 통 제 및 법의 지배의 개선이 농업 생산 증대에 가장 큰 영향을 미친다는 것을 밝혔다.

    ACKNOWLEDGMENTS

    This study was supported by 2017 Research Grant from Kangwon National University(No. 520170184). The authors would like to thank the editor and anonymous referees for the constructive feedback and suggestions that have improved the article.

    Figure

    Table

    Correlation of the GII and the other six governance indicator.

    Definitions and sources of variables.

    Statistic for variables.

    Estimation outcomes of the agricultural production function with governance infrastructure index.

    Estimation outcomes of the aggregated agricultural production function with governance each dimension indicator separately.

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