Private tutoring expenditure: An empirical analysis based on Sri Lankan households

• Published date: 01 August 2018
• Date: 01 August 2018
• Author: Asankha Pallegedara
• DOI: http://doi.org/10.1111/rode.12384

REGULAR ARTICLE

Private tutoring expenditure: An empirical analysis

based on Sri Lankan households

Asankha Pallegedara

Wayamba University, Makandura, Sri

Lanka*

Correspondence

Department of Industrial Management,

Wayamba University of Sri Lanka,

Kuliyapitiya, Sri Lanka and Chair of

Development Economics, Passau

University, Passau, Germany.

Email: asankap@wyb.ac.lk

Funding information

Alexander von Humboldt Foundation

Abstract

This study analyzes private tutoring expenditure in Sri Lanka

using two decades of household survey data combined with

school census data. We use descriptive statis tics and regres-

sion analysis as well as a fac tor decomposition method to

explore the role of variousfactors affecting household private

tutoring expenditure. Empirical results suggest that house-

hold private tutoring expenditure have continuously risen

over the years. The household socioeconomic status is factor

with strong influence and relative importance a ffecting

household private tutoring expenses. There appearsto be eth-

nic disparities in household private tutoring expenditure.

Moreover, results also suggest that spending on private tutor-

ing could be reduced if standardized school teacher rates at a

district level are increased. If the observed trends in private

tutoring continue, they can have social implications for edu-

cation equity, which can undermine the objective of the free

education policy in Sri Lanka.

1

|

INTRODUCTION

Private tutoring is a global phenomenon with demographic, cultural, and economic variations. It is

an informal education system in many parts of the world. It is common, not only in developed

countries, such as the United States, Canada, Japan, and South Korea (Bray, 1999, 2007; Bray &

Lykins, 2012; Buchmann, Condron, & Roscigno, 2010; Davies & Aurini, 2006; Kim & Lee,

2010), but also in developing countries, such as Kenya, China, Sri Lanka, and Bangladesh (Buch-

mann, 2002; Hamid, Sussex, & Khan, 2009; Pallegedara, 2012; Zhang & Bray, 2016). Private

*Also affiliated to Passau University, Germany.

DOI: 10.1111/rode.12384

1278

|

©2018 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/rode Rev Dev Econ. 2018;22:1278–1295.

supplementary tutoring is widely considered as shadow education, since it only exists because of

mainstream education. Usually, when the regular mainstream education system grows or the cur-

riculum in the mainstream education changes, private tutoring also grows or changes its curriculum

(Bray, Zhan, Lykins, Wang, & Kwo, 2014). In some Asian countries, private tutoring is a large

scale education industry. For instance, in South Korea, households spend as much as 80 percent of

government expenditure on public education for primary and secondary students on private tutor-

ing (Kim & Lee, 2010), and in Japan, households spend about 924 billion yen (U.S.$12 billion)

on private tutoring (Dawson, 2010). Similarly, in Singapore, households spent about S$820 million

(U.S.$680 million) on center and home-based private tutoring in 2008, which is an increase of S

$470 million from a decade earlier (Bray & Lykins, 2012).

Private tutoring can have many forms: one-to-one private lessons, small group classes, large

classes, TV, radio, or internet-based tuitions. Tutoring costs for these different forms of private

tutoring are highly varied, usually with more expensive one-to-one tutoring and less expensi ve

large classes with many students. However, the common purpose of any private tutoring is to offer

additional lessons to boost academic performance of the students in exchange for monetary pay-

ment (Bray, 2006; Choi & Choi, 2016). Private tutoring can have social, economic, and educa-

tional implications (Bray, 2009). In most developing countries, it can widen the social inequalities ,

since only the relatively richer households can afford the greater quantities and better quality pri-

vate tutoring, compared with low-income households. From the supply-side perspective, private

tutoring can be a good additional income source for poorly paid public school teachers or univer-

sity students, who conduct part-time private tutoring. However, it can adversely affect main stream

school education, because private tutoring may give school teachers a perverse incentive to teach

badly in regular school classrooms to increase demand for their private tutoring (Jayachandran,

2014). Although extensive private tutoring can adversely affect mainstream school education, pri-

vate tutoring may help academically poor slow learning students to keep up with their peers.

Researchers and policy makers are paying attention to target various aspects of private tutoring,

such as demand for private tutoring and its impact on academic performance. One section of stud-

ies analyzes the factors influencing the demand for private tutoring using individual level or house-

hold level survey data (Azam, 2016; Bray et al., 2014; Kim & Lee, 2010; Tansel & Bircan, 2006;

Zhang, 2014). Results from these works suggest parents’income, perceptions of quality in main-

stream schooling, and competitive examinations to enroll in universities or secondary schools are

main drivers of demand for private tutoring. Another section of research has aimed to reveal the

impacts of private tutoring on academic performance in formal schools using individual student

data (Dang, 2007; Jheng, 2015; Kuan, 2011; Liu, 2012; Ryu & Kang, 2013). These research litera-

ture shows mixed findings on the impact of private tutoring on academic achievement, as some

research finds a positive impact on academic achievement, but others find a negative impact on

formal schooling. This area of research encounters difficulties of measuring the true causal effects

as a result of unobserved characteristics, such as students’motivation and abilities, parents’efforts,

and interpreting the impacts from different types of private tutoring.

Despite the growing literature on the analysis of determinants of private tutoring expenditure,

researchers seldom use both demand-side and supply-side factors to analyze private tutoring expen-

diture. Furthermore, authors are yet to quantify how these factors contribute to disparities in house-

hold private tutoring expenditure. Therefore, this study fills this gap by examining the following

two research objectives. First, this study explores the determinants of private tutoring expenditure

in Sri Lanka by including demand-side factors and a supply-side variable. Second, this study

examines the contributions of each determinant to variations in household private tutoring expendi-

ture using a regression-based decomposition technique. Specifically, we used six waves of

PALLEGEDARA

|

1279