Determinants of Innovation in Laos: A Survey of Micro and ...

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Determinants of Innovat ion in Laos : A Survey of Micro and SmallBusinesses in Vient iane(Determinants of Innovat ion in Laos : A Surveyof Micro and Small Businesses in Vient iane)

著者Author(s) Phonvisay, Alay / Vixathep, Souksavanh

掲載誌・巻号・ページCitat ion 國民經濟雜誌,218(5):77-92

刊行日Issue date 2018-11-10

資源タイプResource Type Departmental Bullet in Paper / 紀要論文

版区分Resource Version publisher

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DOI

JaLCDOI 10.24546/E0041655

URL http://www.lib.kobe-u.ac.jp/handle_kernel/E0041655

PDF issue: 2021-12-14

国民経済雑誌第 218 巻第 5号抜刷

平成 30 年 11 月

Determinants of Innovation in Laos :

A Survey of Micro and Small Businesses

in Vientiane

Alay Phonvisay

Souksavanh Vixathep

77

Determinants of Innovation in Laos :

A Survey of Micro and Small Businesses

in Vientiane

This paper is based on the presentation made by Dr. Alay Phonvisay on January 11th

sponsored by the Keizai-Keiei Gakkai, Kobe University. He received many valuable

comments by the participants, among others by Dr. Souksavanh Vixathep. His com-

ments were constructive enough for the presenter to decide to write a joint paper with

him. The co-authors are grateful to the Keizai-Keiei Gakkai for giving such an opportu-

nity.

Dr. Alay Phonvisay is Deputy Director of Research Division, Assistant Professor at

the Faculty of Economics and Business Management, National University of Laos. He

studied at the Graduate School of International Cooperation Studies, Kobe University,

and acquired the degree of Master of Economics in 2008 and Doctor of Economics in

2011. His research interest is wide-ranging, including industrial policy ; innovation in

SMEs; trade policy ; universal health coverage ; and child health and poverty.

Dr. Souksavanh Vixathep is Associate Professor at the School of Economics / Gradu-

ate School of Economics, University of Hyogo. He studied at the Graduate School of

International Cooperation Studies, Kobe University, where he obtained the doctoral

degree in economics in 2009. His research interests include international trade ; enter-

prises in development ; SME development and entrepreneurship and innovation promo-

tion ; and industrial policy. He has done extensive research on the garment industry in

Southeast and South Asian regions, and innovation and entrepreneurship in SMEs in

Indochina.

Abstract

The Government of Laos has recognized the role and supported the development of

the private sector. This sector is expected to provide employment opportunities to the

young labor force, and contribute to poverty reduction and socioeconomic development.

Following the enactment of the business law in 1994, the role of SMEs which form the

backbone of the private sector has become more relevant to the country’s economy.

Alay Phonvisay

Souksavanh Vixathep

1 Introduction

The economy of Laos has experienced rapid growth in recent time, with an annual growth rate

of seven percent or higher. Yet, economic growth largely relies on extensive resource exports,

which is considered to be unsustainable in the long run. Resource exploitation has undoubtedly

attracted more foreign direct investment, increased exports and government revenue. Along with

the adoption of an open-door policy in the late 1980s, the Government of Laos has recognized the

role and supported the development of the private sector. This sector is expected to provide

employment opportunities to the young labor force, and contribute to poverty reduction and socio-

economic development.

Small and medium enterprises (SMEs) play a crucial role in socio-economic development by

employment generation, contribution to output and growth, export growth, investment, tax reve-

nue, poverty alleviation, economic empowerment and the broader distribution of wealth (Davis et

al., 1993 ; Hallberg, 2000 ; Asasen et al., 2003 ; and Harvie, 2015). SMEs account for between 50

percent and 95 percent of employment in many ASEAN member countries (ERIA, 2014), and

this contribution tends to be proportionally larger from medium sized businesses. It suggests that

their contribution to GDP varies widely across regional economies, between 23�58 percent

第２１８巻第５号78

Upon enacting a decree on SME promotion (Decree No. 42 / PM), the policy on support-

ing SMEs was embedded in the five-year national socio-economic development plans.

Recently, promoting innovation among SMEs has been highlighted in the Lao SMEs

Development Plan 2016�2020. SMEs in Laos still mainly concentrate on the domestic

market. They are mainly domestically owned, lack managerial and technical skills, and

face financial constraints in business operation and expansion, and fierce competition in

an increasingly globalized environment. Overall, SMEs in Laos have experienced a

rapid expansion in the last two decades, increasing in the number (of enterprises) from

3,106 in 1990�1995 to 10,631 in 1996�2000. Considering the important role and contri-

bution of SMEs to economic development in Laos, the proposed study attempts to

address the determinants of innovation. The analysis applies primary data from a self-

conducted questionnaire survey of 200 manufacturing micro and small enterprises in

Vientiane in 2016. The Survey covers the manufacturing subsectors which are catego-

rized into food and non-food sectors. The results indicate that owner education appears

to stimulate some innovation activities, such as introduction of new products which tend

to be new to the market. The findings highlight the importance of human capital on in-

novation in enterprise development.

Keywords Innovation, Human capital, SMEs, Laos

(ERIA, 2014), while Asasen et al. (2003) suggest a figure of between 20�40 percent.

SMEs which form the backbone of the private sector in Laos, mainly concentrate on the domes-

tic market. They are mainly domestically owned, lack managerial and technical skills, and face

financial constraints in business operation and expansion, and fierce competition in an increas-

ingly globalized environment. Overall, SMEs in Laos have experienced a rapid expansion in the

last two decades, increasing in the number from 3,106 (1990�1995) to 10,631 (1996�2000). In

the first decade of the 2000s, the number of SMEs rose by more than 110 percent from 20,966

to 44,916.

Based on the first national economic census in 2006, there were 126,913 enterprises nation-

wide, including 126,717 SMEs or equal to 99.8 percent. There were 196 large enterprises or

equal to 0.2 percent. The total number of labor force is 345,138, including 286,575 people working

for SMEs, or equal to 83.0 percent. Large enterprises employ 58,563 people, or equal to 17.0

percent. Most of the SMEs belong to the trade sector (including wholesale and retail trade and

repair of motorcycles), which represents about 64.5 percent ; followed by the processing industry

sector, representing 19 percent. SMEs are mainly located in Vientiane Capital (22.7％),

Savannakhet province (11.4％) and Vientiane province (10.0％). In Vientiane Capital, the center

of the Lao economy, there were 35,021 enterprises registered, of which micro enterprises

comprise about 83 percent (28,990), while small enterprises make up merely 7 percent (2,265)

of the total number.

Innovation is essential for firms �even more so in the current globalized environment �which

intend to develop and maintain a competitive advantage or to develop a new market (OEDC,

2005; Becheikh et al., 2006 ; Ho and Pham, 2014). The degree of importance of innovation to

competitive advantage is even higher in SMEs than in larger enterprises. The contribution of

SMEs to economic growth is greatly channeled through their innovativeness (Radas and ��,

2009). There exists a view on the role of innovation at the macro- and micro-levels in the econ-

omy. In the former, innovation is deemed to contribute to the nation’s industrial and economic

growth, while in the latter enhances competitive advantage and potential growth of firms (Pham

and Matsunaga, forthcoming).

In literature, the measurement and treatment of innovation differs greatly across academic

disciplines and among the scholars. In Becheikh et al. (2006) innovation is defined as “imple-

mented technologically new products and processes and significant technological improvements

in products and processes’’. In their view (technical) innovation implies a technologically new

product / process or an existing product / process that has undergone a significant technological

Determinants of Innovation in Laos : A Survey of Micro and Small Businesses in Vientiane 79

improvement.

In literature the measure of innovation is treated as a dependent variable in a model and

explained by a set of factors that are considered to influence its change (Bhattacharya and Bloch,

2004 ; Laursen and Salter, 2006 ; Fabrizio and Thomas, 2012 ; Garriga at al., 2013 ; Klingebiel and

Rammer, 2014). Several factors, such as internal and contextual factors, have been addressed in

economics and management literature : firm size (Bhattacharya and Bloch, 2004 ; Klingebiel and

Rammer, 2014), demand structure (Fabrizio and Thomas, 2012), resource allocation and breadth

(Klingebiel and Rammer, 2014).

Considering the important role and contribution of SMEs to economic development in Laos, the

study attempts to address the crucial determinants of firm innovation. The analysis applies

primary data from a self-conducted questionnaire survey of 200 manufacturing micro and small

enterprises in Vientiane in 2016 and several interview surveys in major industrial centers of Laos

(Vientiane, Savannakhet, Pakse). The Survey covers the manufacturing subsectors which are

categorized into food and non-food sectors. It is worth noting that despite the application of a

stratified random sampling procedure, the data obtained during the survey are influenced by the

readiness of enterprise owners for interview.

The remaining of the paper is laid out as follows. Section 2 presents some recent trends of

SMEs. The empirical model and data are described in Section 3. Analysis results are presented

and discussed in Section 4. Section 5 concludes with some policy implications.

2 Laos’ SMEs Overview

In Laos, following the enactment of the business law in 1994, the role of SMEs has become

more relevant to the country’s economy. The first policy to promote SMEs in Laos was found

in the 4th five-year national socio-economic development plan (NSEDP 4). However, in this

very NSEDP SMEs were referred to as small industry and handicraft business. After the 1994

business law, the policy on supporting SMEs was embedded in the five-year national socio-

economic development plans. In the NSEDP 6, the plan aimed to promote SMEs to expand

rapidly, create the conditions to gradually strengthen the financial status of state-owned enter-

prises, including the improvement of their debt situation.

Small and Medium sized Enterprises’ Promotion and Development Office (SMEPDO) was

established in 2005 which has the function of formulating strategies and work plans for the

promotion of SMEs. After that a Five-Year SMEs Development Plan was formulated in 2006. In

2012 SMEPDO was promoted to the Department of Small and Medium Enterprise Promotion


(DOSMEP). In each of the Five-Year SMEs Development Plans since 2006, the policy highlights

the changing ranking of key policy priorities to reflect the rapidly changing contemporary devel-

opments in domestic, regional and global markets. Promoting innovation among SMEs has been

highlighted in the SME Development Plan 2016�2020, and it has been regarded as the top

priority. This policy priority has been harmonized with the strategy on industrialization and

modernization in the Ten-Year Socio-economic Development Strategy (2016�2025).

Prior to 2004 SMEs in Laos were categorized only by the number of employees. In 2004

according to Prime Minister Decree No. 42, SMEs can be categorized by number of employees,

value of assets and sales. Small enterprises are those having an annual average number of

employees not exceeding 19 persons or total assets not exceeding 250 million LAK (Lao Kip, the

currency of Laos) or an annual turnover not exceeding 400 million LAK. Medium sized enter-

prises are those having an annual average number of employees not exceeding 99 persons or total

assets not exceeding 1,200 million LAK or an annual turnover not exceeding 1,000 million LAK.

In order to improve and support SMEs in Laos the SME definition has been refined to be more

diverse by dividing SMEs into three categories namely production, trade, and service in the 2007

revision of the Decree. Moreover, in the most recent revision of the Decree in January 2017, the


Table 1 Number of SMEs in Laos, 1975�2013

Provinces 1975 1975�80 1981�85 1986�90 1991�95 1996�00 2001�05 2006�10 2011�13

Vientiane Capital 67 128 148 707 919 2,975 5,393 13,073 11,542

Phongsaly 1 � 3 19 32 140 263 561 545

Luang Namtha 4 3 6 16 37 223 434 806 702

Oudomxai � 3 6 34 82 333 603 1,483 1,297

Bokeo 1 3 2 25 57 154 316 857 904

Luang Prabang 27 30 50 181 267 920 1,856 3,182 2,568

Houaphanh � 1 5 28 53 204 355 964 808

Xaiyabuly 6 � 21 89 175 517 1,208 3,190 3,025

Xiangkhuang 11 16 8 57 151 269 612 1,595 1,478

Vientiane Province 17 38 36 162 284 892 1,994 4,242 3,566

Bolikhamxai 3 10 13 46 86 358 763 1,645 2,076

Khammouane 4 15 16 60 122 500 1,128 2,246 1,932

Savannakhet 34 39 53 247 373 1,402 2,702 4,662 4,025

Salavan 1 6 6 53 71 233 476 1,140 1,265

Sekong � 1 � 13 31 104 215 456 726

Champasak 50 87 65 229 326 1,227 2,223 3,968 3,230

Attapeu 3 2 2 20 38 180 425 846 1,622

Total 229 382 440 1,986 3,104 10,631 20,966 44,916 41,311

Source : Ministry of Planning and Investment, 2014.

definition of ‘micro-enterprise’ is added to the SME definition. In this new definition of SMEs,

there is no difference between sectors in regard to the number of employees. Micro, small, and

medium enterprises are those having employee not exceeding 5 persons, 6�50 persons, and 51�

99 persons, respectively.

SMEs in Laos have experienced a rapid expansion in the last two decades (Table 1), increasing

in the number (of enterprises) from 3,104 in 1991�1995 to 10,631 in 1996�2000. In the first

decade of the 2000s, the number of SMEs rose by more than 110 percent from 20,966 to 44,916

before declining to 41,311 enterprises during 2011�2013. In 2014, SMEs in Laos are approxi-

mately around 99.8 percent of the total number of firms. Comparing between regions excluding

Vientiane Capital, the central region has larger number of SMEs followed by Northern region and

Southern region. Most of SMEs in Laos are located in major cities, such as Vientiane Capital,

Savannakhet Province, Vientiane Province and Champasak Province ; especially in Vientiane


Table 2 SMEs Classified by Economic Activities (number, ％ share)

No. Economic Activities Micro�enterprise SMEs Total

1 Agriculture, Forestry and Fishery 1,491 672 2,163

2 Mining 68 177 245

3 Manufacturing Industry 11,596 3,861 15,457

4 Electricity, Gas 33 73 106

5 Waste Management 83 81 164

6 Construction 185 430 615

7 Wholesale and Retail 71,683 6,694 78,377

8 Transportation and storage facility 3,106 390 3,496

9 Hotel, and Restaurant 11,599 2,937 14,536

10 Information and Communication 258 111 369

11 Finance and Insurance 214 301 515

12 Property, and Real Estate 623 87 710

13 Professional, Science and Technology 282 125 407

14 Management 568 281 849

15 Security Service 1 7 8

16 Education 84 327 411

17 Health and Social Security 337 84 421

18 Art, Entertainment, and Leisure 592 271 863

19 Other Services 4,420 386 4,806

Total 107,223 17,295 124,518

Percentage share 86.1 13.9 100


Capital which accounted for almost 28 percent or 11,542 firms during 2011�2013.

Considering SMEs by economic activities (Table 2), almost 62 percent belong to the wholesale

and retail sectors, followed by the manufacturing, and hotel and restaurant with 12.4 percent, and

11.7 percent respectively. If enterprises are categorized by the number of employees in a given

year, about 107,223 firms (86.1％) are classified as micro-enterprises in 2013. These micro-

enterprises create roughly 276,441 jobs, which share almost 60 percent of the total 470,602 jobs

created by MSMEs (Table 3). The wholesale and retail sector generate 180,836 jobs, manufac-

turing sector 82,342 jobs, and hotel and restaurant sector 60,438 jobs, respectively. It is interest-

ing to note that among these three sectors SMEs have generate more employment opportunities

in the manufacturing than micro-enterprises, while the latter dominate employment generation in

the other two sectors.


Table 3 Job Creation of SMEs in Laos (number, ％ share)

No. Economic Activities Micro-enterprise SMEs Total

1 Agriculture, Forestry and Fishery 4,820 8,059 12,879

2 Mining 212 2,979 3,191

3 Manufacturing Industry 32,246 50,096 82,342

4 Electricity, Gas 89 1,760 1,849

5 Waste Management 277 1,337 1,614

6 Construction 590 9,075 9,665

7 Wholesale and Retail 180,836 57,354 238,190

8 Transportation and storage facility 8,000 4,883 12,883

9 Hotel, Service, and Restaurant 31,004 29,434 60,438

10 Information and Communication 707 3,209 3,916

11 Finance and Insurance 732 5,376 6,108

12 Property, and Real Estate 1,384 1,311 2,695

13 Professional, Science and Technology 811 1,707 2,518

14 Management 1,700 3,314 5,014

15 Security Service 5 166 171

16 Education 293 6,848 7,141

17 Health and Social Security 913 919 1,832

18 Art, Entertainment, and Leisure 1,645 3,686 5,331

19 Other Services 10,177 2,648 12,825

Total 276,441 194,161 470,602

Percentage share 58.7 41.3 100


3 Analytical Framework and the Survey in Vientiane

3.1 Innovation

Innovation is a complex issue, diversified and continuous process. Enterprises continuously

accumulate new knowledge and constantly modify their products and production processes to

adjust to fluctuating market conditions. Innovation is also considered as a tool of entrepreneurs

to exploit change as an opportunity for a new or a different business and service (Drucker, 1985 ;

OECD, 2005). Innovation is evaluated in different ways. On the one hand, the input-oriented

measurement of innovation uses data on R&D (research and development). But R&D expendi-

ture tends to overestimate innovation, because it includes aborted efforts that do not necessarily

lead to new products / processes or improved products / processes. On the other hand, the output-

oriented measurement applies patent data, innovation count and firm-based surveys. However, a

patent would better represent an invention rather than innovation. The method of innovation

count is deemed an objective approach which relies on innovation data from various sources, such

new product / process announcements, database, journals, etc. (Becheikh et al., 2006).

In empirical literature innovation is commonly represented by number of innovation (Acs and

Audretsch, 1988 ; Fabrizio and Thomas, 2012), number of patents (Lahiri and Narayanan, 2013),

binary variable indicating introduction of a new product / service / process or improved product /

service / process (Bhattacharya and Bloch, 2004 ; Spithoven, Vanhaverbeke, and Roijakkers,

2013), or revenue from new products (radical innovation) and revenue from significantly

improved product (incremental innovation) (Laursen and Salter, 2006 ; Garriga et al., 2103 ;

Klingebiel and Rammer, 2014 ; Love et al., 2014 ; Ozer and Zhang, 2015). For this study a

question was asked whether or not the owner / manager has had a product / service improvement

or introduced a new product / service in the last two years. Hence, a dummy variable, which

represents innovation and indicates the introduction of a new production / process or an improved

product / process, is used as an explained and explanatory variable in the empirical analysis.

3.2 Empirical Model

Adapting from Schumpeter’s theories of innovation, proxies of innovation in this paper com-

prise (i) product improvement, (ii) new product introduction to the firm, and (iii) new product

introduction to market (Schumpeter, 1934).

The empirical analysis applies a methodology for evaluating determinants of productivity using

firm-level data in a production function (Dollar et al., 2005 ; Van Praag and van Stel, 2013).


The productivity equation in Dollar et al. (2005) is expressed as

��

where �is the vector of observable investment climate indicators (available data), �and �are

an unobservable productivity shocks that do and do not affect firm’s input choice.

With some modifications the above model can be applied for determinants of innovation :

��

where �� is a vector of entrepreneur’s characteristics and human capital (gender, education

level, experience), �� denotes a vector of explanatory variables describing the enterprise (firm

age), and ��denotes the statistical error term. The dependent variable describing innovation is

a binary variable of probability of innovation (��).

3.3 The Survey, Data and Variables

A questionnaire survey on micro, small and medium enterprises was conducted in Vientiane

Capital (of Laos) from March to May 2016. The target group is owners or managers of micro,

small, and medium firms in the manufacturing industries. The sampling method is a stratified

random sampling. The survey covers some industrial clusters or production centers in five major

cities of Vientiane Capital. Within an industrial cluster, firms with up to 99 employees (i.e.

SMEs) are selected with equal probability using a stratified random sampling procedure. Also, a

balance between the industrial subsectors and clusters / locations is taken in to consideration. The

samples would well represent the manufacturing industry of Vientiane Capital in terms of indus-

trial subsectors and locations / areas.

In terms of clusters / areas, the survey includes important clusters / areas of Vientiane Capital

in order to have a proper geographical coverage. Regarding the industrial sectors, 17 major

subsectors of the manufacturing industries are included. In sum, the SME Survey-2016 has 200

samples as the initial sample size. Upon data mining, there are 179 samples which can be used

for the analysis. The exclusion of observations is based on the following criteria : (1) incomplete

information on sales, labor, capital, entrepreneur’s education and experience, firm characteristics,

etc.; (2) enterprises with fewer than three employees due to low quality of book keeping ; and

(3) enterprises with more than 99 employees. The definition and description of variables are pre-

sented in Table 4. From the filed survey, it shows that the average sales of SMEs in Vientiane

Capital are about 508 million LAK and the capital equipment is roughly 363 million LAK (See

Note 3 in Table 5 for exchange rate). A representative SME would hire 13 employees in 2015


and the average firm’s age is 11.8 years.

In Table 5, roughly 42 percent, 69 percent, and 70 percent of the respondents report that they

have achieved in improving the existing product, introducing new product to the firm, and intro-

ducing new product to the market, respectively. The average age of entrepreneur in Vientiane

Capital is 41 years. The majority of SME owners / managers have completed at least secondary

school education (about 55％).

4 Results and Discussions

The probability estimation (Probit model) is applied to evaluate determinants of innovation

activities. All the variables are derived from one-year data (one-point data). Table 6 presents the

result from the Probit models and their average marginal effects for all three innovation activities.


Table 4 Definition of Variables from the Survey Data

Variable Definition / description

Innovation

improve Dummy variable for product improvement firm, and equals 1 if true

new to firm Dummy variable for new product introduction to the firm, and equals 1 if true

new to market Dummy variable for new product introduction to the market, and equals 1 if true

Characteristics of entrepreneur

age Age of entrepreneur (years)

male Dummy variable for male entrepreneur, and equals 1 if true

higheredu Dummy variable for university-level education or higher level, and equals 1 if true

lhsedu Dummy variable for lower and higher secondary education, and equals 1 if true

vocatedu Dummy variable for vocational education, and equals 1 if true

uptoprimedu* Dummy variable for not attending school to having completed primary school, and

equals 1 if true

trader* Dummy variable for being trader prior to start-up, and equals 1 if true

farmer Dummy for being farmer prior to establishing the business, and equals 1 if true

nonsoeworker Dummy variable for having worked in a non-state enterprise prior to start-up, and

equals 1 if true

soeworker Dummy variable for having worked in a state-owned enterprise prior to start-up,

and equals 1 if true

Characteristics of enterprise and product

food Dummy variable for food production enterprise, and equals 1 if true

firmage Age of the firm which equals 2016 minus year of establishment

firmage 2 Squared term of firm age (firmage 2＝firmage*firmage)

Note : The asterisk (*) denotes the reference variable.

Overall, human capital variables (higher education) appear to determine innovation activities

of SMEs. However, human capital variable only shows statistical significance in innovation model,

namely introducing new product which is new to the market (Table 6, Column 3). A correlation

matrix is presented in the appendix (Table A1) to confirm that there is not collinearity problem

among independent variables.

The estimate for university education is positively significant for the innovation activity, such

as introducing new product to the market. This result implies that entrepreneurs with university

education have a higher probability of achieving introduction of a new product which is new to the

market, as compared to their counterparts with primary education. The result implies that high

human capital tends to enhance innovative activities in manufacturing firms in Vientiane. This

result is consistent with the findings in previous studies for both developing countries (for


Table 5 Summary Statistics

Variable Obs. Mean Std. Dev. Min Max

improve 179 0.422 0.495 0 1

new to firm 179 0.688 0.464 0 1

new to market 179 0.700 0.469 0 1

age 179 41.1 10.4 22 90

male 179 0.441 0.498 0 1

higheredu 179 0.274 0.447 0 1

lhsedu 179 0.274 0.447 0 1

vocatedu* 179 0.296 0.458 0 1

uptoprimedu* 179 0.156 0.364 0 1

trader* 179 0.363 0.482 0 1

farmer 179 0.112 0.316 0 1

nonsoeworker 179 0.162 0.369 0 1

soeworker 179 0.095 0.294 0 1

firmage 179 11.8 9.3 1 59

food 179 0.416 0.494 0 1

lnfirmage 179 2.159 0.831 0 4.077

lnfirmage2 179 5.349 3.450 0 16.626

Source : Authors compiled from survey data.

Notes: 1. Monetary variables are denoted in 1000 LAK (Lao Kip, local currency)2. The asterisk (*) denotes the reference variables in the regressions.

3. The official exchange rate for 2016 was 8,129 LAK＝USD 1.00.

Pakistan (Kurosaki and Khan, 2004); Laos (Onphanhdala and Suruga, 2010 ; Vixathep, 2017);

Vietnam (Santarelli and Tran, 2013 ; Vu, 2014 ; Vixathep et al., 2017)) and developed economies

(for Ireland (Pickels and O’Farrell, 1987); Netherlands (Van Praag and Cramer, 2001 ; Parker

and van Praag, 2006)).

In addition, human capital addresses the effect of work experience prior to the start-up. The

analysis compares work experience in farming, state-owned and non-state enterprises to the

reference group (trader). Statistical insignificance of coefficients for work experience implies


Table 6 Determinants of Innovation in MSEs (Vientiane)

Probit for Innovation (marginal effect)Improve New to Firm New to Market

Variables dy/dx dy/dx dy/dx

lnage �0.162 0.047 �0.252

(0.176) (0.167) (0.166)male (*) 0.102 �0.007 0.008

(0.079) (0.074) (0.073)higheredu (*) �0.058 0.122 0.182*

(0.125) (0.107) (0.096)lhsedu (*) �0.144 �0.016 0.038

(0.113) (0.111) (0.102)vocatedu (*) �0.065 0.017 0.118

(0.115) (0.106) (0.094)farmer (*) �0.018 �0.029 0.022

(0.125) (0.118) (0.107)soeworker (*) 0.163 0.1 0.101

(0.136) (0.118) (0.112)nonsoeworker (*) 0.041 �0.007 �0.05

(0.111) (0.1) (0.105)food (*) 0.093 �0.214*** �0.021

(0.079) (0.073) (0.074)lnfirmage 0.133 0.073 �0.184

(0.181) (0.166) (0.182)lnfirmage2 �0.011 �0.022 0.042

(0.042) (0.039) (0.042)Observations 179 179 179

Log-likelihood �117.03 �104.14 �103.78

Pseudo-R2 0.038 0.063 0.053

Notes : 1. Standard errors in parentheses.

2. *** p＜0.01, ** p＜0.05, * p＜0.1

3. (*) dy / dx is for discrete change of dummy variable from 0 to 1.

4. Log-likelihood is Log-pseudolikelihood for the Probit regression.

that having experience as worker in the technical area do not seem to stimulate innovation in

SMEs in Vientiane.

Interestingly, food manufacturing firms in Vientiane are less likely to implement innovation

activity, as compared to the other type of manufacturing firms (non-food). The estimate for com-

paring food manufacturing firm to the other type of manufacturing firms is negatively significant

for innovation activity of introducing new product which is new to the firm (Table 6, Column 2).

The result implies that products in non-food manufacturing firms are of more varieties and more

flexible to adopt new changes comparing to products in food industry. However, other determi-

nants, such as entrepreneur age or gender, and firm’s characteristics (firm’s age), show no statis-

tical significance with all types of innovation activities.

5 Conclusions

The Lao economy has experienced high growth over the past decade. However, growth in the

past has been largely driven by the resource sector. In order to achieve sustainable growth the

manufacturing sector should be improved. SMEs have played an important role in promoting the

industrialization and generation of employment opportunities for the workforce. With a young

private sector, many of the SME owners are first-generation entrepreneurs, and their human

capital and social capital are the two most important factors that enhance their entrepreneurship.

This study addresses the essential role of education on innovation for micro and small busi-

nesses in Vientiane Capital as a case study. It re-confirms the positive relationship between

human capital and innovation, and emphasizes the importance of education for SME-sector devel-

opment as part of economic development.

In interpreting the results in this paper one should bear in mind the limitation that the explana-

tory variables in the empirical analysis only cover entrepreneur’s education and work experience,

and the firm age. Therefore, adding more variables of human and social capital, firm and industry

characteristics to the regression analysis would undoubtedly improve the results and findings.

This represents one of the main issues for the extension of the study.



Tab

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ma

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�0.092

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�0.377

1.000

up

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��0.181

�0.042

�0.264

�0.264

1.000

farm

er��0.081

�0.101

�0.218

0.1000.1401.000

soew

ork

er�0.2250.0960.015

�0.028

�0.035

�0.115

1.000

non

soew

ork

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�0.135

0.1280.070

�0.066

�0.064

�0.156

�0.142

1.000

lnfi

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�0.011

0.0380.041

�0.040

0.1650.024

�0.225

1.000

lnfi

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0.190

�0.048

0.0570.029

�0.036

0.1450.037

�0.212

0.9641.000

voca

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0.0550.040

�0.398

�0.398

�0.279

0.0030.0400.047

�0.045

�0.0561.000

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0.139

�0.016

�0.203

0.0310.155

�0.268

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�0.332

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