Landlockedness, Corruption, and Economic Growth in BIMSTEC

This paper presents a macroeconomic growth model to explore the impact of landlockedness and corruption on economic growth rate of BIMSTEC. The BIMSTEC bridges South East Asia to South Asia, or ASEAN to SAARC, or blue economy to mountain economy. The analysis concludes that landlockedness reduces the economic growth rate. It hints a signiﬁcant augmentation in trading cost, cross border cost, and poor access to the coast in the region. Corruption plays grease in the wheel situation. The non-monotonous behavior reveals that it only works below 49 points of CPI. After this threshold level it will turn into sand in the wheel . Control variables are obvious for this model too. Hence, the study preserves myriad scope of economic trade-transaction among the members and with the globe. Each members of the county has been practicing their own economic policies for economic development, but sometimes it is not suﬃcient. Economic development is also induced by regional access and agreements. In the context, it strongly recommends two policies. the regional take liberal policies against rigid, and weak Second, landlocked countries easy access to the transactions to

1 Introduction ital in developing countries. Ade et al. (2011) establish that a low level of corruption inflows a significant amount of FDI. Also, it leads to inequality higher and hurts the poorer than the rich classes (Gyimah-Brempong, 2002).
Furthermore, governmental corruption may also discourage private investment by raising the cost of public administration since it is likely to take the form of a bribe for public service or by generating social discontent and political unrest-which may lead to economic growth (Alesina et al., 1996). On contrast, Huntington (1968), and Friedrich (1972) have suggested that it is also plausible factor for economic well-beings. They argue that if the government has produced a package of pervasive and inefficient regulations, then corruption may help circumvent these regulations at a low cost. Under this scenario, it is possible that corruption may improve the efficiency of the system and help economic growth. In the situation of weak governance and rigid bureaucratic, corruption works like grease in a squeaking wheel (Mondiale, 2006).
In the same token, Mauro (2004) explains that the effect of corruption depends on the different equilibria of rent-seeking activities. It is positive in case of high economic growth with the high prohibition of week governance and bureaucratic system, however, a bad balance with high corruption and low economic growth. Also, Méndez and Sepúlveda (2006) express that the relationship between corruption and economic growth is nonmonotonous-quadratic behavior. Regarding the BIMSTEC members, we can't gainsay that they are free from the institutional rigid bureaucratic system, weak governance, and rent-seeking behavior. It geographically intersects the two economies: the blue economy and the mountain economy. That shows a lucid picture of some kind of geographical cost too. Therefore, the paper caries a genuine issue that what is the impact of landlockedness and corruption on economic growth rate of BIMESTC? Corruption plays dual behavior on income:none is linear and another is the quadratic or non-monotonous. Therefore, the study tries to reveal the both effects. The study is immense important regarding trust, policy, FDI inflow, international transaction, access to equal trade, bureaucratic system, macro-economic stability and so on.
The remaining parts of this paper are arranged systematically. Second section is literature survey of numerous empirical and theoretical judgments. The third section tells us about the data and strategies applied in the paper. The fourth section is the empirical result and its economic analysis. The final section is the conclusion, it also provides a brief policy implications.

Literature Surveys
The literature review of this paper is precisely categorized into two distinct parts. The first part is an overview of landlockedness and economic growth rate. The second part is an overview of corruption and economic growth; this part is further sub-divided into three distinct approaches based on the effects of corruption.

Landlockedness and Economic Growth
Most of the literature have revealed the negative relationship between landlockedness and economic growth. For instance, World Bank (2014) estimates that the level of development in LLDCs is 20 percent lower on average than the non-landlocked. Individual country estimates show the ranges of development costs for most LLDCs that ranges from 10 to 30 percent. Paudel (2014) scans the determinants of economic growth in developing countries within the standard growth regression framework, with special attention being paid to the experience of landlocked developing countries (LLDCs). The results claim that the landlockedness hampers economic growth rate. Bhattarai (2019) examines whether landlockedness has any impact on the exporting capacity of landlocked countries among a panel data analysis of 104 countries including 30 landlocked countries. Finally, the researcher displays that landlockedness has a substantially adverse impact on the trading capability of the landlocked countries. Also, landlocked countries need foreign investments than any other geographical groupings. However, most landlocked developing countries (LLDCs) have failed to attract FDI on enough scale to offset poor local factor endowment and accelerate economic development with capital imports (Adams, 2009). Faye et al. (2004) unearth that landlocked countries not only face the challenge of distance, but also the challenges that result from dependence on passage through a sovereign transit country, one through which trade from a landlocked country must pass to access international shipping markets. The study also finds that landlocked countries have a 9 percent higher ratio of export and insurance cost to the actual value of the exports compared to its maritime neighbors. The issue of trade facilitation becomes even crucial for landlocked countries. A study by Stone (2001) unveils that out of 30 landlocked countries, 18 have transport costs higher than import trade value in Africa. Similarly, 7 countries out of 15 transportation cost exceeding 20 percent. Another important discovery by Nuno and Venables (1999) is that the median landlocked country has transport costs 58 percent higher than the median coastal economy. Mellinger et al. (2000) observe that the majority population who are far from the sea coast, have been bearing large transport costs for international trade. Similarly, the population of tropical regions have high disease burden are the another obstacles for the economic growth and development of those countries. Coastal economies have a high per capita income than landlocked.
They have noted the huge transport cost counted for landlocked countries which is the special case of geography linking with economic progress.

Corruption and Economic Growth
Approach First: Sand in the Wheel The first approach assumes that corruption reacts like sand in the wheel. The literal meaning of it is that corruption leads to theft and fraud by public officials for private wealth accumulation. It leads to loss of net capital of the economy and decreases national output (Alam, 1989). Regarding corruption and income relation, most of the literature is skewed toward this approach. For instance, corruption impairs economic growth (Mauro, 1995;Venard, 2013), total investment and foreign direct investment (Wei, 2000), and both public budgets and the productivity of a county's infrastructure (Tanzi and Davoodi, 1997). It also harms on revenue collection-in particular tax revenues-can be lower (Aghion et al., 2016). Ultimately, it hampers in budget size and investment of the economy. Similarly, in African countries, a unit increase in corruption reduces the growth rate of GDP and per capita, and increases income inequality (Gyimah-Brempong, 2002). Rotimi et al. (2013) also find that corruption damages economic growth in Nigeria. Chene (2014) reveals that corruption is likely to adversely affect long-term economic growth through its impact on investment, taxation, public expenditures, and human development. Gyimah-Brempong and DeGyimah-Brempong (2006) supplement that corruption affects the equitable distribution of resources across the population, increasing income inequalities, undermining the effectiveness of social welfare programs, and ultimately re-sulting in lower levels of human development. To add, corruption is likely to weaken the citizen trust in institutions and processes. An expanding strand of the literature shows that low trust amongst households can lead to lower financial inclusion and lower stock investment (Guiso et al., 2009). Trust is also important in the cross-country context; perceptions of low trustworthiness across countries are associated with lower trade, foreign direct investment, and portfolio investment in severe cases, corruption can undermine trust in the government, inciting civil unrest and conflict; more uncertainty can harm investment and other economic activity (Tanzi and Davoodi, 1998).
Approach Second: Grease in the Wheel Some literature have argued for sand in the wheel, however, there are numerous arguments on greasing in the wheel hypothesis too. The hypothesis declares that corruption can have a positive impact on economic growth rate by compensating for a bad and rigid governance. Corruption is chosen as a second-best solution to economic and structural problems that arise either due to the over regulation of a weak institutional environment (Lee and Oh, 2007;Huntington, 1968;Marquette and Peiffer, 2015). Furthermore, Heckelman and Powell (2010) opine that corruption can be growth-enhancing when economic freedom is limited, but the positive effect disappears with higher degrees of economic freedom.
Approach Third: Non-Linear Relationship Thach et al. (2017) scrutinize the impact of corruption on economic growth by using data from 19 Asian countries for 12 years, 2004 to 2015, with DGMM data processing techniques and quantile regression. The results show that corruption is a hindrance to the economic growth of those Asian countries. To add, economic growth is impacted by different levels of the corruption at different quantiles, unambiguously, at the quantile level from 0.1 and 0.5, corruption impacts positively on economic growth, or vice versa, from the level of 0.75 and 0.90, it is negative. Correspondingly, Sindzingre et al. (2010) reveal that corruption is beneficial at a low level of incidence and detrimental at high levels of incidence. Mallik and Saha (2016) reflect that corruption is not always growthinhibitory, for some countries it is growth-enhancing which supports the greasing the wheels hypothesis in the sample of 146 countries but not for all. Similarly, Ahmad et al. (2012) show that a decrease in corruption raises the economic growth rate in an inverted U-shaped way.

Data and Estimation Strategy
The issue of this study is cracked under inferential statistics using panel database. It contains seven cross-section-Nepal, India, Bhutan, Sir Lanka, Bangladesh, Myanmar, and Thailand-and seven-time series observation from 2012-2018. The raised issues are solved utilizing the principle variables-GDP growth rate, corruption, squared of corruption, and landlockedness (categorical variable)-and few control variables: gross fixed capital formation, remittance, and labor force. GDP growth rate is hired as the proxy for economic growth rate, and gross fixed capital formation is for investment.
Landlockedness is measured by a dummy variable (L 1 ). Where, L 1 = 1 refers the presence of Landlocked economies, that are Nepal and Bhutan, and 0 for other coastal economies.
Similarly, there are three indices to demonstrate the corruption size in the economy: the International Country Risk Guide (ICRG), Corruption Perception Index (CPI) by Transparency International (TI), and the World Bank's Corruption Control Index (Baliamoune-Lutz and Ndikumana, 2010). In the paper, CPI is used to demonstrate the corruption level. Likewise, the labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. The inflation rate is computed from the consumer price index.
CPI is sourced from the Transparency International, and remaining other variables are hired from the World Bank. The variables: remittance and gross fixed capital formation are measured as a percentage of GDP, and the labor force variable is measured in 100 million. Utilizing the guidance by Baltagi (2008), and Gujarati (2009) the functional format of the model starts from equation (1) and followed by a non-linear regression as given by equation (2): In the non-linear transformation The variables used in this research are non negative. Furthermore, the partial derivative of equation (2) is expected the following signs: Lank, and Thailand have modest corruption; however, Myanmar, Nepal, and Bangladesh are relatively more corrupted and score a range from 23 to 30 (among 100) CPI averagely.

Result and Discussion
In this regard, Bhutan is the least corrupted country, which achieves more than 60 CPI on an average. Likewise, Figure 2    This is the optimum point of greasing in the wheel. It demonstrates that as well as corruption perception index goes down, it induces economic growth. On the contrary, the square of CPIs' coefficient reveals that the greasing in the wheel will turn into sand in the wheel after a threshold level, is 49 points of corruption perception index. Similarly, 0.592 percent economic growth of the BIMSTEC is responsible when it adds one million labor force to the existing labor market. The economic growth rate is positively influenced by 0.11158 and 0.1569 percent respectively for a one percent increment of remittance and investments' share to GDP. These are very obvious findings for any growth model.

Conclusion
This paper presents a macroeconomic growth model to explore the impact of landlockedness and corruption on economic growth rate of BIMSTEC. The BIMSTEC bridges South East Asia to South Asia, or ASEAN to SAARC, or blue economy to mountain economy.
The analysis concludes that landlockedness reduces the economic growth rate. It hints a significant augmentation in trading cost, cross border cost, and poor access to the coast in the region. Corruption plays grease in the wheel situation. The non-monotonous behavior reveals that it only works below 49 points of CPI. After this threshold level it will turn into sand in the wheel. Control variables are obvious for this model too. Hence, the study preserves myriad scope of economic trade-transaction among the members and with the globe. Each members of the county has been practicing their own economic policies for economic development, but sometimes it is not sufficient. Economic development is also induced by regional access and agreements. In the context, it strongly recommends two policies. First, the regional agenda of BIMSTEC should take liberal policies against rigid, corrupted, and weak governmental-bureaucratic system. Second, landlocked countries of the region should get easy access to the coast for lubricated economic transactions to the overseas. Trend of Inflation Rate

Supplementary Files
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