2021-09-21_tom tat luan an_tieng anh_kyten

Microsoft Word CVHon Tom tat luan an EN 280222 MINISTRY OF EDUCATION AND TRAINING CAN THO UNIVERSITY o0o SUMMARY OF DOCTORAL DISSERTATION Major Finance – Banking Major code 62340201 CAO VAN HON IMPACT[.]

MINISTRY OF EDUCATION AND TRAINING

CAN THO UNIVERSITY

-o0o -

SUMMARY OF DOCTORAL DISSERTATION

Major: Finance – Banking Major code: 62340201

CAO VAN HON

IMPACTS OF CREDIT RATIONING ON THE AMOUNT OF CAPITAL ALLOCATED TO INPUTS AND ON RICE YIELD OF FARMERS

IN THE MEKONG RIVER DELTA

Can Tho, 2022

THE RESEARCH WAS COMPLETED AT

LIST OF PAPERS RELATED TO THE DISSERTATION

Domestic magazine

1 Cao Van Hon and Le Khuong Ninh (2019) Impact of credit rationing on rice yield of farmers in the Mekong River Delta Asian journal of Economic and Banking, No 160, pages 44-

56

2 Cao Van Hon and Le Khuong Ninh (2020) Impact of credit rationing on capital allocated

to inputs used by rice farmers in the Mekong River Delta, Vietnam Journal of Economics of Development, Vol.22 No.1, pp 47-60

Proceedings of the international conference

1 Cao Van Hon and Le Khuong Ninh (2019) Impact of credit rationing on rice yield of farmers in the Mekong River Delta International conference on Business, Economics & Finance held at Can Tho University, December 2019

2 Cao Van Hon and Le Khuong Ninh (2020) Geographical distance and access to bank credit of rice farmers in Vietnam” International conference on Business, Economics & Finance held at Can Tho University, December 2020

Chapter 1 INTRODUCTION

1.1 IMPORTANCE OF THE RESEARCH PROBLEM

The Mekong River Delta is a key rice production area of Vietnam Each year, it contributes over 50 per cent of the total rice output and account for about 90 per cent of the exported rice (Statistical Yearbook, 2018) That achievement is the result of the Mekong River Delta being accreted by a large amount of alluvium from the Mekong River pouring into Vietnam through two tributaries of Tien and Hau rivers The Mekong River Delta is also favored by nature in terms of climate with harmonious rain and sun, helping irrigate and wash away harmful pathogens on crops In general, the Mekong River Delta has enough natural conditions to increase rice productivity and output However, the reality shows that most of the farmers only focus on production without paying attention to preparing enough capital to buy factors (or agricultural inputs) and develop output markets to ensure good prices for products while these markets fluctuate very unpredictably Therefore, rice farmers in the Mekong River Delta face many challenges because of their small production scale They often face the problem of fluctuating output prices, while the cooperation among the relevant agents (i.e., the state, scientists, businesses, and farmers) is very weak As a result, rice farmers remain poor because

of low and precarious income, especially when the effects of climate change become more and more obvious

Due to low income, farmers cannot afford to buy inputs following production requirements

in terms of quantity, quality and time, leading to low productivity and the income of farmers Therefore, farmers want to borrow but are often denied access to credit due to asymmetric information and limited liability, which result in risk for credit institutions Consequently, only some rice farmers get enough credit while others are given just a proportion of their requests or completely rejected despite being willing to pay higher interest rates Then, credit rationing emerges as described by Stiglitz and Weiss (1981), among others Due to credit rationing, a number of rice farmers do not have enough capital to acquire inputs for production so as to achieve maximum rice yield They may, then, contemplate two options, i.e., using less of all inputs (the scale effect) or less of the inputs that are not much vital to rice yield (the substitution effect) Reducing the number of inputs will not prevent diseases and ensure the essential nutritional needs of rice, so the yield is low and the quality of rice seeds is not satisfactory In other words, the above phenomenon lowers productivity and product quality as compared to the case of no credit rationing as demonstrated by the theories (Feder, 1985; Lee and Chambers, 1986; Carter, 1988; Fare et al., 1990; Carter and Niebe, 1990; Blancard et al., 2006; Ciaian et al., 2012)

The above analysis shows that capital is very important for agricultural production, but farmers are credit-rationed due to asymmetric information and transaction costs, which affects their production Therefore, this is a topic that needs to be explored to serve as a scientific and practical basis for sustainable agricultural development policies However, according to our

knowledge there have not been any in-depth studies on the relationship between credit rationing and the amount of capital allocated to inputs and rice yield of farmers in the country in general and in the Mekong River Delta in particular Therefore, the topic “Impacts of credit rationing on the amount of capital allocated to inputs and rice yield of farmers in the Mekong River Delta” was selected by the author

1.2 RESEARCH OBJECTIVES

1.2.1 General objective

The purpose of this dissertation is to estimate the impact of credit rationing on the amount

of capital allocated to inputs and on rice yield of farmers in the Mekong River Delta to propose solutions to help the farmers better use capital for production and improve rice yield

1.3.2 Research scope

The thesis studies the effect of credit rationing on the amount of capital allocated to inputs and rice yield of farmers in the Mekong River Delta, including the provinces/cities of An Giang, Bac Lieu, Ca Mau, Can Tho, Hau Giang, Kien Giang, Soc Trang, Tra Vinh and Vinh Long at two time points of 2015 and 2018 to verify the science and practicality of the research problem that the thesis is interested in

1.4 CONTRIBUTION OF THE THESIS

1.4.1 Theoretical aspect

The dissertation builds a theoretical basis on the impact of credit rationing on the amount

of capital allocated to inputs and the impact of credit rationing on rice yield of farmers This

theoretical basis is built mainly on the principles of Microeconomics and Microfinance with an application the credit sector, especially agricultural and rural credit

1.4.2 Practical aspect

The results of estimating the effect of credit rationing on the amount of capital allocated to inputs and on rice yield of farmers in the Mekong River Delta are a scientific ground with a practical value This result helps scientists and policy makers to devise policies for sustainable agriculture and rural development

In addition, the nonlinearity in the effect of credit rationing on the amount of capital allocated to inputs and on rice yield of farmers in the Mekong River Delta is also a new contribution of high scientific value This helps scientists as well as policy makers guide farmers

to use the optimal amount of inputs to improve productivity and income while protecting people's health and the natural environment

Chapter 2 LITERATURE REVIEW

Chapter 3 THEORETICAL BACKGROUND AND RESEARCH METHODOLOGY

3.1 THEORETICAL BACKGROUND

3.1.3 Theoretical background of the impact of credit rationing on the amount of

capital allocated to inputs

Credit rationing leads to insufficient capital to buy inputs for production, so rice farmers

must contemplate how to allocate the available capital to inputs so as to minimize this adverse

effect To model that behaviour, the thesis is based on the arguments developed by Debertin

(2012) Firstly, let consider a rice farmer who aims to minimize production cost due to credit

rationing imposed by the credit institution This farmer’s production function is y  f ( M , N ),

with y being rice output and M, Nbeing inputs Then, the farmer’s minimum cost of

given a constraint of y 0 f(M,N), where PM and PN are the price of M and N, respectively

To minimize the cost, the following Largangian expression can be used:

y0 f ( M , N )NP

0 0

f P N

f P

N

f P M

f P

M

N N N

M M M

M

f

f P

P  or

N

N M

M

P

f P

f  (3.6)

In Expression (3.6), f is the marginal productivity of input M M and f /M PM is the

marginal productivity of one dong invested in input M Similarly, f / the marginal N PN

productivity of one dong invested in input N According to a principle of microeconomics,

N N

M

f /  / means production cost is minimized given output y0 , so profit is maximized

If credit markets are perfect, the source of financing is irrelevant or rice farmers have full access

to credit (Foltz, 2004) In other words, rice farmers get sufficient capital to acquire inputs in

order to produce the output that minimizes production cost and maximizes profit conforming to

Expression (3.6) However, because rural credit markets are virtually imperfect due to information asymmetry and transaction cost, leading to advserse selection and moral hazard and causing risk for the credit institution (Stiglitz và Weiss, 1981) As a result, it rations the amount

of credit granted to rice farmers, so the latter does not have enough capital to buy the amount of inputs that satisfies Expression (3.6) Then, the scale effect emerges, affecting the scale of input use but not the relative input intensities – a phenomenon called symmetric credit rationing In concrete, the scale effect corresponds to the case in which farmers reduce both M and N, so rice yield definitely plunges Besides the scale effect, there also exists the substitution effect that affects both the level of input use and their relative intensities since more credit rationed inputs will be substituted by less ones (asymmetric credit rationing) In both cases, due to credit rationing rice farmers use an amount of inputs deviating from what is supposed to be the most efficient (i.e., maximizing profit)

Moreover, the impact of credit rationing on the amount of capital allocated to inputs used

by rice farmers are nonlinear because the marginal productivity varies according to the level of inputs applied Therefore, to estimate the impact of different degrees of credit rationing, in addition to identifying the treatment effect of using credit using the propensity scores, this paper also estimates the treatment effect of heterogenous intensities of credit rationing facing rice farmers

3.1.4 Theoretical background of the effect of credit rationing on rice yield of farmers

To build the theoretical framework of the impact of credit rationing on rice yield of farmers, the thesis is based on the arguments developed by Blancard et al (2006), and Ciaian et al (2012)

To do that, a representative profit-maximising farmer with a possibility for input credit rationing

is taken into consider ation

This farmer’s production function is y f( NM, ), with y being rice output and M, Nbeing inputs and farm’s profits function are:

N P M P N M

 (3.7) where, p are output price and PM, PNare input price M, N

Due to credit rationed, farmer have C amount of money to buy inputs The value of Cconstrains the amount of inputs that farmers can use for production through the inequality:

C N P M

PM  N 

 (3.8) where α and δ are dummy variables which distinguish farmer with credit rationing between inputs (M and N) If 1 and  1, it implies a symmetric farm’s credit rationing for both inputs M and N If a farmer only credit rationed with one input, it implies an asymmetry in credit rationing, i.e., 1 and 0 (credit rationing affects only M) or 0 and  1 (credit rationing affects only N)

Farmer maximises profits subject to credit rationing (3.8) according to LaGrangean:

)(

),

The optimal conditions for a credit rationing farm are as follows:

M

M

P M

f p

N

N

P N

f p

M and N If without credit rationing (0), farmers will have enough production capital (with non-binding credit C ) and the marginal value product of both inputs M and N is equal to the input price itself (pf M PM and pf N PN) This result shows that without credit rationings, farmers will maximize profits according to the common principle in microeconomics that marginal revenue is equal to marginal cost ( MR  MC ) However, due to credit rationing, farmers do not have enough capital to produce at the above optimal level, so rice yield will be negatively affected

If a farmer is credit rationed both inputs (  1 ,   1 and 0) from equations (3.10) and (3.11), follows that the marginal value product of both inputs is higher than the price of inputs in equilibrium if a farm is symmetrically credit rationed: pf M PM and pfNPN If a farmer is credit rationed only input M ( ,10) and   0, the marginal value product M is higher than the input price itself ( pf  M P M ) and the marginal value product N is equal to the input price itself (pfNPN) Similarly, If a farmer is credit rationed only input N ( ;01) and   0, pf M PM and pf N PN Thus, if credit rationed of both inputs is the marginal value product of both inputs is higher than the price of inputs in equilibrium Then, farmers could potentially increase its profits by increasing input use but they cannot do so because of credit rationing

On the basis of the theory presented previously, to make it easier to visualize, in Figure 3.1 the vertical axis shows the quantity of input N and the horizontal axis shows the quantity of input M used in production Without credit rationing (   0 ), farmers have enough money C

to buy the amount of inputs that satisfies expressions (3.10) and (3.11) Then, the optimal output corresponds to the point D where the relative marginal value product of inputs M and Nis equal

to their relative market prices

N M

Asymmetric credit rationing

Consider the case of a farmer is credit rationed for one input Specifically, farmer is credit rationed as to input M ( 1 and   0) or input N (  0 and   1) Due to the credit ration, farmers only have the amount of money C1 (C 1 C) to buy inputs Then, the amount C1 with the rationing in the expression (3.8) makes ( 1 0 ) The binding credit C1 affects one of the farm’s equilibrium conditions (3.10) and (3.11), depending on which input is credit rationed

In Figure 3.1 credit rationing shifts of the isocost curve from EE to EASEAS , and isoquant from I to II This scale effect of an asymmetric credit rationing shifts the equilibrium from D

to F, which is the tangent point between isocost EASEAS and isoquant II Isoquant II is below I

implying a lower output with than without the binding (asymmetric) credit rationing

At the same time, expressions (3.10) and (3.11) imply that:

AS j i AS

j i K j i K

j

i

P

P C

pf C pf P

P C

pf

C

) ( ) ( )

(

)

(

1 1



where input i is assumed to be credit rationed and the K -index is not credit rationed

As a result, asymmetric credit rationing changes the relative marginal value product of inputs by the shadow price of credit rationed input 1 In response to this, a farm substitutes the credit rationed input for a credit un-rationed input because

AS j i

K j

M p

p ) 1

(  1 , with

AS N

M i K N

M

P

P P

P (1) The rotation takes place until point B, which is determined by the credit rationing C1, by way to move point F to point B This result is called the substitution effect

In summary, an asymmetric credit rationing reduces the equilibrium output, decreases the credit rationed input, and may increase or decrease the credit un-rationed inputs Farmers expand the use of the credit non-rationed inputs, if the substitution effect dominates the scale effect In

the reverse case, if the substitution effect is smaller than the scale effect, then farmers reduce the use of the credit non-rationed inputs

Symmetric credit rationing

Symmetric credit rationing (   1 ,   1 ), a farmer is equally rationed with respect to both inputs Assume that the farmer can only borrow the amount C2 (C2 C1 C) so the isocost curve shifts from EE to ESES The optimal production point in this case is A (Figure 3.1) – that is, the tangent point between isocost ESES and isoquantIII Credit rationings on two inputs have no effect on the relative marginal product value between the two inputs because

S j i S

j i K

pf

C pf

In summary, the theoretical model of the effect of credit rationings on the amount of capital allocated to inputs shows that credit-rationed farmers change the way they allocate capital to inputs Specifically with the scale effect, farmers reduce capital allocation for both inputs Farmers with substitution effect may allocate more capital to the non-credit rationed input and less to the credit rationed factor than in the non-credit rationed case Similarly, credit-rationed farmers have lower rice yields than non-credit-rationed farmers In addition, when credit rationings increase, the production productivity of farmers decreases

On the basis of the theory just presented, the goal of the thesis is to estimate the effect of credit rationing on the amount of capital allocated to inputs and to estimate the effect of credit rationing on rice yield of farmers in the Mekong River Delta Specifically, the thesis estimates the difference in the amount of capital allocated to inputs (varieties, fertilizers, pesticides and hired labor) and estimates the difference in rice production (yield) expressed by isoquant II vs I

of Figure 3.1 (when credit-rationed farmers compared to the non-credit-rationed) and the isoquant III versus the isoquent II of Figure 3.1 (when credit-rationed farmers is less than the other credit-rationed farmers)

3.1.5 Research framework

Figure 3.2 Proposed Research Framework

CREDIT RATIONING AMOUNT OF CAPITAL ALLOCATED TO INPUTS OF RICE PRODUCTION

(Seeds, fertilizers, pesticides, and hired labor)

RICE YIELD

Factors (land area, income, time living in the

locality, age of household head, education,

gender of household head, distance, position of

household head, and experience)

3.2 RESEARCH METHODS

3.2.1 Data collection method

To achieve the set objectives, the thesis uses both primary and secondary data For secondary data, the thesis uses data from relevant agencies such as the General Statistics Office, Provincial People’s Committees, Provincial Statistics Departments, the State Bank branches in the Mekong River Delta provinces, and related research at home and abroad

The empirical model specified previously requires data on the determinants of access of rice farmers to credit and variables capturing the amount of capital allocated to inputs used by them The data used in this paper were collected through direct interviews with heads of 1,017 rice farmers in 2015 and 1,065 in 2018 randomly selected out of 9 provinces and cities in the MRD (Table 3.1) through the questionairs modified after several pilot surveys

Table 3.1 Survey sample structure

Local

Number of farmers

proportion (per cent)

Number of farmers proportion

1065 rice farmer in 2018, which allows us to employ a semi-parametric propensity score matching (PSM) estimator PSM is commonly used in empirical studies (e.g., Rosenbaum and Rubin, 1983; Bento et al., 2007; Roberts and Key, 2008; Briggeman et al., 2009; Pufahl and Weiss, 2009; Katchova, 2010; Ciaian and Kancs, 2012) due to its ability to control the selection bias by constructing the counterfactual The advantage of the PSM estimation method is control the sampling bias

3.2.2.1 Impact of credit rationing on the amount of capital allocated to inputs

Based on the abovementioned arguments, this paper specifies an empirical model to estimate the impact of pertinent factors on credit rationing facing rice farmers in the MRD as follows:

i i i

i i

i

i i

i i

i

erience tion

socialposi ce

dis gender

education

age residence

income land

oning creditrati

5

4 3

2 1

0

(3.12)

In Model (3.12), the dependent variable (creditrati oningi) is constructed based on the ratio

of the amount of credit granted to the farmer and the amount of credit he has applied for (borrowratei) If borrowratei 1, there is no credit rationing, so (creditrati oningi) has a value of 0 If

1

0  borrowratei , there is credit rationing, so (creditrati oningi) has a value of 1 The independent variable (landi) is the farmer's area of rice production, measured in 1,000m2 The variable (incomei) is the average income of household, measured in million VND/year The variable (resedencei) is the time the farmer has lived in the locality, measured in years The variable (agei)

is the age of the household head, measured in years The variable (educationi) is the schooling of household head, measured in years The variable (genderi) is the gender of household head, if the head of household is male, the variable (genderi) takes the value 1, otherwise (genderi) takes the value 0 The variable (distancei) is the distance from the farmer's house to the nearest credit institution, measured in km The variable (socialpositioni) is a dummy variable, if the head of household has relatives, acquaintances working in state agencies or political organizations and vice versa, the variable (socialpositioni) takes the value 1, otherwise the variable (socialpositioni) takes the value 0 The variable (experiencei) is the number of years engaging in farmer's rice production, measured in years

Model (3.12) will be estimated using Probit estimator to identify the propensity score Based on propensy score matching identified, the thesis use the kerrnel comparision method to identify the impact of credit rationing on the amount of capital allocated to inputs used and rice yield of farmers

To provide a more precise picture of the impact of credit rationing on the amount of capital allocated to inputs used and rice yield of farmers, this paper uses the method conducted by Ciaian and Kans (2012) to divide the sample into 6 categories with descending degrees of credit rationing Specifically, the first category includes rice farmers with 0  borrowratei 0 , 2, category

2 with 0,2 borrowrate 0,4, category 3 with0 , 4  borrowrate  0 , 6, etc, Then compare category

2 with category 1, category 3 with category 2, etc

3.2.2.2 Method to estimate the effect of credit rationing on the amount of capital of farmers

PSM is employed to determine the difference between the treatment and the control, which

is called the average treatment effect on the treated (ATT), after controlling for differences