bad luck or bad budgeting: an analysis of budgetary roles underpinning poor municipal fiscal...

Bad Luck or Bad Budgeting: An Analysis ofBudgetary Roles Underpinning Poor Municipal

Fiscal Conditions in Thailand

WEERASAK KRUEATHEP

This research examines the causes of the poor fiscal condition of Thai municipalitiesduring 2001 and 2006. A mixed analytical approach is employed. First, the researchquantitatively singles out fiscally distressed municipalities from a set of sampledcities. The findings show that central cities and semi-rural areas were fiscally weak.Then, two cases of disparate fiscal conditions are qualitatively analyzed. In contrastto those of the healthy city, budget actors in the fiscally weak city failed to followdesignated budgetary roles. The paper recommends that improved budgetary roles inThai cities be promoted so that their fiscal performance is secure.

INTRODUCTION

For the past two decades Thailand has attempted to promote local fiscal autonomy and the

devolution of service responsibilities to the hands of local governments. Within 12 years of the

devolution, the ratio of total local revenues to that of the national government leaped from 13.4

percent in 1999 to about 26.8 percent in 2012 (Ministry of Finance of Thailand 2012). Despite

increasing fiscal resources, many empirical studies find that many Thai municipal governments

still face several financial difficulties—particularly those governments with restricted tax bases

and a concentration of low-income populations (Suwanmala 2001; Varanyuwatana 2003;

Patmasiriwat 2006; Krueathep 2010a, 2010b).

Notwithstanding, the current study contends that apart from the poor socioeconomic

conditions of cities, poor budget practices committed by concerned budget actors can cause a

deterioration in municipal purses. Therefore, this article explores how good and bad budgeting

deeds affect a city’s fiscal condition, given that a city’s socioeconomic setting has been taken

Weerasak Krueathep, Ph.D., in Department of Public Administration, Faculty of Political Science at the

Chulalongkorn University, Henri-Dunant Road, Patumwan District, Bangkok 10330, Thailand. He can be reached

at [email protected].

© 2014 Public Financial Publications, Inc.

Krueathep / Bad Luck or Bad Budgeting 51

into consideration. This research is significant for Thailand and other countries undergoing fiscal

decentralization in that it helps to identify potential financial management problems before they

develop into full-blown fiscal crises.

The paper begins with an overview of municipal administration in Thailand. It then discusses

analytical frameworks and data collection procedures. The quantitative findings of Thai

municipal fiscal conditions are presented in a subsequent section. Next, the performance of

budget actors underpinning a city’s healthy or poor fiscal condition is examined through two

qualitative contrasting cases. Finally, the article concludes with some policy implications for the

improvement of municipal fiscal administration.

OVERVIEW OF MUNICIPAL ADMINISTRATION IN THAILAND

Municipal governments in Thailand are self-governing bodies similar to those of other nations.

The decentralization movement has significantly shaped municipal operations and institutional

arrangements in several ways. Firstly, all municipalities are now governed by the mayor-council

form. The executive and the council members are both directly elected from local constituents.

The executive is responsible for preparing local development policies and budgets, which are

ultimately reviewed and adopted by the council. In addition, municipal operations are monitored

by the local council, the Department of Local Administration (DoLA) and the Office of the

Auditor General (OAG), a national, independent auditing agency.

Secondly, municipal governments have three major tax/revenue sources: (i) locally collected

taxes/revenues; (ii) shared taxes and local taxes/revenues collected by central government

agencies; and (iii) intergovernmental fiscal transfers. Locally collected taxes/revenues

constituted approximately 9.7 percent of the total budgets during FY 2001 and FY 2012,

whereas the portion of shared taxes and municipal revenues collected by central agencies were

52.4 percent on average during the same period. Revenues from intergovernmental fiscal

transfers were about 37.9 percent.

Finally, major service responsibilities of municipalities are presently appearing in a general

fund and are classified into six categories: (i) public safety; (ii) education; (iii) public health; (iv)

housing, public works, and community services; (v) social and public welfare; and (vi) general

administration and law enforcement. Most of these services are provided across all

municipalities in accordance with budget guidelines from the DoLA.

ANALYTICAL FRAMEWORKS

Amixed analytical approach is employed in the current research. Firstly, the study quantitatively

measures fiscal conditions of sampled cities. This procedure is employed in order to single out

fiscally weak and healthy cities from the rest. Then, two in-depth cases of distinct fiscal

conditions discovered by the quantitative findings are qualitatively analyzed so that the budget

management issues underlying the healthy or weak fiscal conditions unfold.

52 Public Budgeting & Finance / Fall 2014

In measuring Thai municipal fiscal conditions, the research applies the need-capacity

framework developed by ACIR (1962, 1988), Bradbury (1982), Ladd and Yinger (1989), and

Rafuse (1990) due to its robust properties. Theoretically, it adequately captures institutional

arrangements and environmental factors that give rise to local fiscal conditions. These aspects

are often argued for in the fiscal condition literature (e.g., Bradbury 1982; Ladd andYinger 1989;

Zafra-Gomez et al. 2009). Practically, the need-capacity framework is flexibly adjustable to fit

within the Thai local fiscal context and has already provided credible pictures of Thai municipal

fiscal conditions consistent to the U.S. experience, especially during the 1970s and 1980s

contexts (e.g., Krueathep 2010a, 2010b).

The need-capacity framework consists of two intertwined elements: the estimation of

revenue-raising capacity (RRC) and expenditure need (EN). First, Martinez-Vazquez and Boex

(1997a, 1997b) and Dye (1984) have provided a measure for analyzing the RRC, namely

regression-based RRC. Regression analysis allows for the computation of potential municipal

revenues based on statistical relationships with a set of socioeconomic factors and proxies of a

city’s tax base. The predicted amount of revenue that follows from the regression represents the

potential revenue that each city can collect under the average tax effort.1 Estimation procedures

for the RRC are elaborated in Appendix A.

Second, the analysis of the EN follows the measure developed by Ladd and Yinger (1989).

This measure has one crucial strength in that it takes into account service cost differentials in

estimating the expenditure need (Bradbury 1982; Bradbury et al. 1984). The estimated EN

represents the potential spending level for each of the service functions in a city, given average

service quality and the scope of service responsibilities. A city’s variation in the EN, then, occurs

when its cost index is higher or lower than other comparable cities.2 Details of the procedures for

estimating the EN are shown in Appendix A.

The final step of measuring municipal fiscal conditions is the calculation of a municipal fiscal

health index (FHI). Ladd and Yinger (1989) quantify the FHI from the difference between the

RRC and EN, expressed as a percentage of capacity. Algebraically,

FHI ¼ ðRRC� ENÞ=RRC� 100 ð1Þ

1. In this study, five major municipal taxes/revenues were selected as the bases for estimating RRC; namely, (i)

value-added taxes (VAT); (ii) land and real estate transfer fees; (iii) excises and alcohol taxes; (iv) commercial land

and building taxes; and (v) user fees/charges. This is because they constitute more than 90 percent of total municipal

revenues, excluding intergovernmental transfers, and have been levied uniformly across cities in Thailand. Hence,

they can well depict the city’s taxing capacity, even though some of them are centrally collected for tax

administration purposes as once argued by Olowu and Smoke (1992).

2. The estimation of EN focuses on general-fund spending, consisting six service functions: (i) public safety; (ii)

education; (iii) public health; (iv) housing, public works, and community services; (v) social and public welfare; and

(vi) general administration. Arguably, this approachmight distort the fiscal condition analysis as contended byWang

et al. (2007). Notwithstanding, unlike most cities in the United States where a substantial portion of general services

are listed in separate public funds, the general fund expenditure of Thai cities constitutes a large portion of municipal

activities. Thus, it is less likely to cause a significant bias of the estimation of the EN.


The FHI identifies a city’s relative ability to finance its service responsibilities as compared to

the sampled cities, given the city’s economic, social and demographic characteristics. The index

has a base value of zero. A positive index implies a city’s taxing capacity is greater than its

expenditure needs, suggesting that the city’s fiscal condition is relatively healthy.

After measuring Thai municipal fiscal conditions comes the analysis of budgeting causes

underlying the healthy or poor fiscal positions via a case-study approach. Here, the current

research grounds its analysis in the Wildavsky’s (1975, 1984) budgetary roles framework by

arguing that fundamental issues of poor fiscal conditions stem from the deviancy of budget actors

from their appropriate budgetary roles. The selected framework is of utmost importance for

Thailand where budget actors do not have a definite view regarding their appropriate roles

(White and Smoke 2005). This approach will help to provide concrete guidelines on how each

budget actor might assist in improving fiscal conditions.

According to Wildavsky (1984), the term “role” is defined as “the expectation of behavior

attached to institutional positions” (160). He classifies budgetary roles broadly as that of “budget

guardian” and a “spending advocate.” Later on, Schick (1988), Aarsaether (1990), and Good

(2007) expanded these roles to incorporate a “priority setter” and a “financial watchdog”; where

the former refers to an ordering of policy choices based on ideological preferences, normally

performed by elected officials and the latter is to monitor public spending against established

accounting and financial standards.

SAMPLE AND DATA

This study focuses on a fiscal condition analysis ofmajor cities located in the vicinity of Bangkok

and in the eastern region. This is because most cities in these two regions, when compared with

the rest of the nation, vary considerably and have experienced rapid social and economic changes

in recent decades. Thus, they are a good candidate for fiscal condition analysis. The scope of

study constituted 22 municipalities in a sample. A two-sample t-test analysis showed that they

did not differ from other major cities throughout the country in terms of the population size (F-

statistic¼ 1.4, p-value¼ 0.239).

The research started with sending an invitation letter to the mayors of all 22 cities in order to

invite them to participate in the study and 14 cities agreed to join.3 Data for the quantitative

analysis were compiled mostly from primary sources (city profiles, the city’s medium-term

strategic plan, annual financial reports, and budget documents). Numerical data incorporated

municipal revenues and expenditure, socioeconomic variables, and the like, covering the period

from FY 2001 to FY 2006. All monetary figures were at constant prices in 2000 and the

expenditure figures include current and capital spending. Like previous research (e.g.,

3. This was an important step since most of the needed data were available at the municipal level, not from other

secondary sources. Thus, the alternative strategy for data collection was the author’s visits to all cities and collecting

the data from primary sources, resulting in a relatively small sample size. Hence, permission to access to the needed

data had to be secured from the city mayors and relevant municipal officials.


Wasylenko and Yinger 1988), a three-year moving average of capital expenditure has been used

in order to cope with the uneven nature of investment decisions from year to year.

After quantifying the 14-cities’ overall fiscal condition over time, two cases of each of the

cities’ fiscal conditions—fiscally strong and fiscally weak—were explored in order to gain a

deeper insight regarding their fiscal condition symptoms. Here, they were given fictional names

so that the anonymity of the cities and key informants were preserved.4 Qualitative case data

were obtained via personal interviews, field work and non-participant observations of routine

municipal activities. Furthermore, relevant documents such as town hall meeting minutes and

media and local newspapers were consulted in order to delineate critical issues regarding taxes

and city services. These multiple data sources were triangulated in order to check the validity of

the information compiled from one data source to another.

Table 1 shows that the 14 cities varied considerably in terms of population size, spending per

capita and economic and population changes from 2001 to 2006. Based on socioeconomic

orientation, these 14 cities can be classified into four major groups. The first group of cities is

highly urbanized, with a median population of 167,464. Next, five suburban cities skirt the

central and heavy-industrial zones and have a median population of 55,269. Another four are

small, semi-rural cities, having a median population of 18,722. The last group of cities is quite

unique in that these cities are situated in economically concentrated areas. The analyses that

follow rely on the city classification just discussed.

THAI MUNICIPAL FISCAL CONDITIONS

Following the procedures for estimating the municipal fiscal conditions discussed above, the

RRC, EN, and FHI of the 14 sampled cities are presented accordingly. First, for the estimation of

RRC, Table 2 shows that cities with relatively large economic endowments or industry-based

cities (group 4), had about two times higher RRC per capita (or 8,601.1 Thai baht) than the

average city in FY 2006. Semi-rural cities (group 3), on the other hand, had the lowest RRC per

capita throughout the period of study (about 3,028.0 baht), or about 62 percent to 72 percent of

the average city in FY 2001 and FY 2006, respectively. This makes reasonable sense since their

socioeconomic conditions might not be able to yield much tax revenue. Likewise, large, highly

populous central cities (group 1) exhibited relatively low tax capacity of about 3,457.5 baht per

capita, although their capacity had been improving drastically during the previous five years, or

more than 237 percent increase from FY 2001 to 2006.

Next, Table 3 presents the cost indices of six service programs for each of the four city groups.

Cost index depicts how financially difficult a city would face in providing average quality of

services, giving its levels of input prices and socioeconomic contexts. The baseline value in 2006

4. Key informants included city mayors, council members, budget directors and officials in charge of relevant

operating units. Neighborhood leaders and interest group representatives were also interviewed. Interviews usually

lasted between 30 and 60 minutes. An audio recorder was not used as most discussion involved suspicious financial

management practices of city government in which the key informants were working.


TABLE1

MajorCharacteristics

ofCitiesin

theStudy(A

ctualData

inFiscalYear2006)

[1]Major

characteristics

(no.ofcities)

[2]Majoreconomic

activities

[3]Average

pop.size

(pop.density)

[4]Average

totalspending

per

capita

(operating

expenditure)

[5]Economic

growth

(2001–2006)

(%,constant

prices)

[6]Population

growth

(2001–2006)

(%)

1.UrbanCity(3):highly

urbanized

cities;

residential

areas

adjacentto

Bangkok

Commercial

(retails;

wholesales);

service-related

businesses;

governments;and

educations

167,464(5,256)

4,090.4

(2,765.2)

4.9

�1.6

2.SuburbanCity(5):

urbanized

areas,

suburban

toindustrial

zones

Commercial

(retails;

wholesales);

smallscaleindustries

55,269(4,436)

6,219.8

(3,843.0)

39.6

�8.5

3.Sem

i-ruralCity(4):

semi-rural,residential

areas

Commercial

(retails);

agriculture

and

agricultural

processing

18,722(4,482)

7,148.1

(4,754.3)

46.3

5.4

4.Industry-basedCity

(2):highly

economic

concentrationareas

Tourism

,service

industries,commerce;

andlarge-scale,

heavy

industries

70,438(364)

16,334.4

(6,068.6)

55.1

20.0

Sample

Average

48,577(4,048.6)

8,716.6

(4,778.7)

30.8

1.0

NationalAverage

45,698(4,108.5)

n.a.

31.8

0.9

Note:Approxim

ately32Thaibahtisequivalentto1USD(asofDecem

ber,2013).Monetaryfiguresareatcurrentprices,calculatedonapercapitabasis.A

veragepopulation

sizesaremedianvalues.Populationdensity

isthenumber

ofpopulationper

onesquarekilometer.

Sources:Datawerecompiled

from

primary,localsources.Thenational-level

datawas

taken

from

theOffice

ofNational

Economic

andSocial

DevelopmentBoardof

Thailand;n.a.refers

tonotavailable.


is set to 100, and the figure above the basemeans that a city requiresmore resources on average in

order to fulfill its service obligations (e.g., higher labor costs, high population density, or a larger

portion of the poor, etc.). Table 3 reveals that central cities tended to have higher service costs

than the other groups of cities for all service functions, except for education. For instance, public

TABLE 3

Public Service Cost Indices and City’s Expenditure Needs

City group

2006 Cost indices fora

2006

EN

indexa

2001

EN

indexbPublic

safety

Education

(K-12)

Public

health

Housing &

community

services

Social

welfare

General adminis-

tration

1. Central 208.1 109.9 160.4 193.5 161.2 184.9 112.7 80.2

2. Suburb 68.5 71.5 78.9 49.6 86.3 60.1 73.9 30.6

3. Semi-rural 86.5 88.8 71.7 67.7 81.4 61.6 92.0 33.5

4. Industry-

based

106.6 149.8 127.4 131.1 129.5 134.6 158.1 113.8

Average 110.7 96.4 103.5 99.5 109.1 100.7 100.0 57.4

S.D. 70.9 36.3 49.8 74.1 43.5 67.5 41.9 47.4

Min. 27.2 41.5 54.2 12.4 60.9 22.2 40.6 13.2

Max. 304.2 197.6 240.5 288.7 207.0 248.5 204.8 169.8

Note: EN stands for expenditure need.aThe baseline for the expenditure need index in 2006 was set equal to 100.bThe baseline in 2001 was set equal to 57.4, representing the proportion to the level of EN of 2006.

TABLE 2

Regression-Based Revenue-Raising Capacity

City group

2006 2001

Average

percentage

changes

(FY 01-06)RRC

Relative

to the

means RRC

Relative

to the

means

1. Central 3,457.5 82.3 1,322.4 65.8 237.2

2. Suburb 3,589.6 85.5 1,291.8 64.3 183.5

3. Semi-rural 3,028.0 72.1 1,234.4 61.5 157.1

4. Industry-based 8,601.1 204.8 5,991.7 298.3 43.5

Average 4,200.5 100.0 2,008.7 100.0 169.2

S.D. 2,032.1 1,824.2 113.1

Min 2,578.9 613.1 43.4

Max 9,435.3 6,566.2 468.6

Note: RRC stands for revenue-raising capacity and is shown as Thai Baht per capita (about 32 baht is equivalent to 1USD, as

of December 2013). FY stands for fiscal year.


safety in central cities cost twice as much as the average as indicated by an index value of 208.1

relative to the average of 110.7 in FY 2006. This finding is fairly congruent with those of Ladd

(1992), Ladd and Yinger (1989) andWarner and Hefetz (2002) where higher density cities were

more likely to have higher service costs.

In a similar vein, industry-based cities had a tendency to have more expensive service costs

than the average, especially for education and housing and community services. Here industrial

cities would demand an extra half of their resources to finance quality education as compared to

the average city. Being located in industrial zones would entail city governments to provide

better schooling such that more skilled workers could meet a competitive market expectation. In

contrast, suburbs were better off than the average city in that they exhibited relatively lower cost

indices for most service functions.

The last two columns of Table 3 also present the indices for EN only for FY 2001 and FY

2006. Following the instruction given by Ladd and Yinger (1989), a baseline for the EN index

was set at 100.0 and the value above the baseline signifies that a city needs more fiscal resources

to fulfill its standardized package of services. The table shows that central cities exhibited a

rather high spending need in 2006, or about 12.7 percent above the norm. Industrial cities also

demanded a higher level of expenditure need, about 58.1 percent to the average, for a similar set

of city’s services. By contrast, residents in suburbs tended to have a significantly lower level of

service needs than the average, about 26.1 and 26.8 index points below the norm in FY 2001 and

2006, respectively.

Finally, Table 4 depicts the city’s fiscal health indices (FHI) of FY 2001 and FY 2006. The

FHI indicates that central cities were greatly distressed for the whole period of the study (see

TABLE 4

City Fiscal Health, Fiscal Year 2001 and Fiscal Year 2006

2006 2006 2006 2001

RRC(baht) EN index

Converted

EN(baht)

Fiscal Health

Index

Fiscal Health

Index

City group [1] [2] [3] [4] [5]

1. Central 3,457.5 112.7 4,734.8 �39.8 �182.3

2. Suburb 3,589.6 73.9 3,104.0 14.7 17.1

3. Semi-rural 3,028.0 92.0 3,866.0 �29.5 �5.8

4. Industry-based 8,601.1 158.1 6,642.3 24.3 36.0

Average 4,200.5 100.0 4,200.5 �6.6 �33.4

S.D. 2,032.1 41.9 1,761.8 40.9 126.3

Min. 2,578.9 40.6 1,704.6 �102.6 �301.6

Max. 9,435.3 204.8 8,602.1 39.7 62.6

Note: RRC stands for revenue-raising capacity and is shown as Thai Baht per capita (about 32 baht is equivalent to 1USD, as

of December 2013). EN is expenditure need and FHI is fiscal health index. A positive FHI value indicates a relatively healthy

fiscal condition.


column 4). For instance in FY 2006, they lacked approximately 40 percent of their capacity to

fulfill service needs as compared with other city groups. Likewise, semi-rural cities had

relatively weak fiscal conditions in the same fiscal year. About 30 percent of fiscal resources

were needed if the level of service provisions were to be fulfilled. On the contrary, industry-

based cities were fiscally strong, having about 24 percent of capacity higher than needed in FY

2006. Similarly, suburbs also had a moderately strong fiscal position, having capacity about 15

percent more than need. In light of these findings, Thai municipalities in the large central cities

and in the semi-rural based areas tend to have financial difficulties in meeting their service

obligations, as compared to the suburbs and industry-based cities.

EXPLAINING POOR FISCAL CONDITIONS: BAD LUCK OR BAD BUDGETING?

In order to explain the potential causes of poor municipal fiscal conditions, one fiscally healthy

city and one fiscally weak city were contrasted with regard to their political, fiscal and service

delivery profiles. The first case, which shall be named “East Sea Beaches,” is a tourism-industry

city that possesses healthy fiscal conditions. It exhibits relatively accountable politics and

budgeting and serves as a benchmark for the other case as to how perverted budgetary roles are

attributed to fiscal instability. The second case, the so-called “Tree Jasmine,” depicts the

opposite scenario. It is a semi-rural community and possesses the dual conditions of poor socio-

economy and municipal budgeting. While structural conditions give Tree Jasmine bad

socioeconomic luck, its corporatist politics and bad budget practices put the municipal finances

into a worse-case scenario.

Case Study One: East Sea Beaches Tourism City

City’s Socioeconomic Bases. The City of East Sea Beaches was incorporated in 1978 and is now

one of the renowned tourism destinations of Thailand. It covers an area of 208.1 square

kilometers or roughly 80.35 square miles and is equipped with 15-km long, golden sand beaches

and many tourist attractions. The population of the City is about 105,000 (FY 2007) and grew

approximately three percent yearly during 2000 and 2007, whereas the national population

growth rate was about 0.9 percent per year during the same period.

The city economy consists mainly of hotel and tourism industries as well as recreation and

related services and approximately four to five million tourists visit the city each year. As of

2007, 87 percent of the labor force were working in the hotel, services and manufacturing

industries. The average annual income of the city residents was about 2.8 times higher than that

of the national average during 2000 and 2007.

Fiscal and Service Delivery Policy. As a hub for tourism and service businesses, the City has

invested drastically in terms of economic and public infrastructures. Furthermore, the City’s rich

economy has made it virtually free of crime. During 2000 and 2006, the nation’s overall crime

rate was 7.2 per 1,000 population on average, whereas that of East Sea Beaches was about 1.4 per


1,000 people. Over time, the City has put itself at reasonably low fiscal pressure, maintaining a

budget surplus of about 5.9 percent from FY 2001 to 2006 and having accumulated reserve of

about 53 percent of its annual spending.

Despite its rich economic conditions, the City puts great effort into maintaining its healthy

fiscal conditions from aggressive tax efforts and through the control of excessive service

provisions. For instance, in FY 2002, the City levied a new tax scheme, which was extremely rare

among Thai localities, for the construction of a new wastewater treatment plant. In terms of its

spending, on the other hand, the City responded to constituency demands within a viable budget

framework. In one case of the making of the FY 2008 budget requests; for example, the director

of the City’s new hospital of 60 beds estimated hiring 300 FTE staff, including physicians and

certified nurses. However, the Mayor cut staff levels to 100 since he viewed the request as

disproportional to the hospital’s physical and fiscal capacity. Additionally, in respect to

educational services, the City tries to run its schools in consistent with constituency demands and

the municipal purse. It runs 11 schools in FY 2007, from kindergarten to K-12, with a student

enrollment of 11,418 students. There were 750 teachers and teaching assistants to serve 304

classrooms. On average, a ratio of a municipal student to city population was about one to nine.

This ratio is important for comparison with City of Tree Jasmine which will be showed later.

Politics and Administration Behind the City’s Fiscal Condition. Since the city’s incorporation,

formal political authority in East Sea Beaches has long been occupied by a single political group

named Raksa East Sea Beaches (RESB) (a fictional name) for about 27 years. The RESB is well-

regarded as fiscally conservative and having strong political support from both inside and nearby

jurisdictions. In effect, political continuity enables the city executives to generate a coherent set

of policy priorities and to smooth the implementation of key development programs. There was

no need for escalating municipal spending in order to forge political allies.

One might suspect that political stability might cause an undesirable impact on the city’s

administrative governance. Yet, this was not the case in East Sea Beaches. Several checks and

balance mechanisms were promoted in order to help energize the municipal bureaucracy of

1,971 FTE staff (1,580 city employees and 391 school personnel, as of July 2007). For instance,

the city executives tried hard to engage the public in municipal affairs. Citizen participation via

town hall and neighborhoodmeetings was widely encouraged in order to help the city executives

prioritize constituency needs. Media and local business groups in East Sea Beaches were also

energetic and influential in monitoring the work of the municipal government. They regularly

monitored the operations of the City and were ready to call the City mayor if anything went

wrong or was suspicious. Finally, the City Council played a tough role in examining the

municipal operations and keeping the City’s fiscal house in order.5 Furthermore, audit

mechanisms worked quite effectively in improving the city operations and finances. The City’s

5. This can be reflected from the author’s personal non-participant observations in one of the general assembly

meetings of the Council (duringNovember 12, 2009, 13.30–15.00 p.m. and 16.00–17.00 p.m.). Council members did

their best in questioning the executives regarding service policies, disputable tax collections, management of assets

and the results of some service programs.


internal audit unit was well equipped with qualified staff and external audits were routinely

checked by the Office of Auditor General (OAG).

All in all, the City of East Sea Beaches possessed good fiscal conditions through its supportive

socioeconomic environment and its politically and administratively well-run organization. A

large part of this admirable story is attributable to the fact that the city’s budget actors performed

well in their designated budgetary check and balance roles.

Case Study Two: Tree Jasmine Semi-Rural City

City’s Socioeconomic Bases. The City of Tree Jasmine was incorporated in 1935 and covers an

area of 8.43 square kilometers or about 3.26 square miles. In 2007, the city population was

19,927 and the city’s land for residential and commercial zones is about 1.99 square kilometers

or about 23.9 percent of its total area. The rest is for arable and non-utilized lands. By national

standards, Tree Jasmine is considered to be a semi-rural area.

The City’s economy mainly consists of few small-scale industries which hire about a 350

labor force in total and about 1,700 retail businesses, most of which are mom-and-pop types. Its

economy grew annually by about two–three percent (real terms), with a population decline of

about 1.1 percent per year from 2001 to 2006. Overall, the residents are distinctly poor. Gross

city products per capita in Tree Jasmine were around 68.9 percent of the national figures between

2001 and 2007. As appeared in the reports from civic forums since 2000 and the author’s

interviews with civic leaders, the major concern of city residents is poverty. They really need

poverty reduction and job promotion programs from the city government.

Fiscal and Service Delivery Policy. Not only did the city’s poor economy contribute to its poor

fiscal condition but its low tax effort, poor tax administration, and too generous services also

impeded fiscal adaptations to fit the meager socioeconomic environment. First, the City was

quite passive in raising municipal taxes. Elected officials often feared that tax mobilization

would have a detrimental effect on their political popularity. As the City Mayor stated, “No one

here loves taxes, but services. If possible, I would give up the collection of trash collection and

some other fees and provide all needed services free of charge to residents. Then, I would ask for

more financial support from the central government.” (City Mayor of Tree Jasmine, personal

interview with author, October 6, 2009).

Such a low tax effort mentality may seem politically rational when considered from a

common-pool resource lens (Rodden 2002, 2006). Notwithstanding, the practice of lowering

taxes in Tree Jasmine came with huge costs in terms of a weakened municipal purse. First, “The

political executives often asked for unreasonable tax exemptions or deductions for their political

cliques beyond those allowed by law” (Former Finance Director of Tree Jasmine, personal

interview with author, June 23, 2009), said the former Finance Director. They were so intrusive

in municipal tax administration that quite often, tax collectors were given the political order to

never file any delinquency case to the tax courts.

Accounting malpractices also worsened the fiscal condition of city hall. In the handling of tax

delinquency cases; for instance, tax/fee receivables were not accounted for by appropriate


accounting procedures. Instead, the receivables were simply written-off at the end of the fiscal

year because doing so was more convenient than carrying on the receivable accounts for

10 years. Although this practice was once noticed by the OAG’s audit team, the city executives

felt that they need not follow the OAG’s recommendations.

On the expenditure side, city executives tried to increase popularity and political allies

through generous educational services as compared to East Sea Beaches and to the other 12 cities

included in this study (see Table 5). This has been evident since the coming of the current City

Mayor in 2004. For instance, the portions of educational spending of Tree Jasmine (column 1)

rose radically from about 35.4 percent in FY 2001 to about 57.2 percent in 2006, or about 11.4

percent growth annually. On the contrary, the educational spending portions of East Sea Beaches

(column 2) ranged from 9.7 percent in FY 2001 to 21.6 percent in FY 2006, or about 16.2 percent

on a six-year average.

On the surface, the education priority would be acceptable politically and fiscally if it nicely

fits local demands and if its financing schemes are viable. Notwithstanding, analyses of the

City’s Strategic Plans 2001–2005 and 2006–2010 indicated that the education programs did not

rank high on the constituents’ list nor were the city’s educational resources being spent

efficiently. As already discussed, the majority of communal residents in Tree Jasmine

experienced poverty and poor living standards. Still, the amount of the city budget allocated for

job training and occupational promotions was trivial, about 1.0 percent to 1.2 percent of the

municipal budget during FY 2001–2007. Nevertheless, the City Mayor counter-reasoned that:

“Education was a top priority since our city did not have a lively economy nor did it have

expansive job markets. Thus, we would be better off spending on a child’s education and

development than on boosting the local economy.” (City Mayor of Tree Jasmine, personal

interview with author, October 6, 2009).

TABLE 5

Portions of Annual Budget Allocated for Educational Programs

Fiscal

year

City of

tree

jasmine

(%)

City of

East Sea

Beaches

(%)

Other

Semi-

Rural

Cities (3

cities) (%)

Central

cities (3

cities) (%)

Industry-

based

cities (1

cities) (%)

Suburbs

(5 cities)

(%)

Sample

averagea

(12 cities)

(%)

[1] [2] [2] [3] [4] [5] [6]

2006 57.2 21.6 44.3 24.9 11.4 26.3 35.4

2005 45.0 13.9 38.1 26.1 8.8 22.5 32.4

2004 50.7 13.8 41.1 21.5 7.7 21.4 24.4

2003 39.2 10.9 35.2 20.2 5.0 22.0 25.4

2002 41.4 27.0 44.6 17.4 8.8 28.1 27.8

2001 35.4 9.7 42.9 15.8 9.6 18.1 26.3

aFigures exclude those of the City of Tree Jasmine. Figures in parentheses indicate the number of cities being compared to

those of Tree Jasmine.


Arguably, that the education spending was so massive might be because of a shortage in

educational supply. However, detailed analyses show that school shortage was not the case in

Tree Jasmine. Total school supply in the jurisdiction was abundant compared to the size of the

City’s youth population of about 4.7 thousand. In FY 2007, the City ran six schools, four were

K-9, with a student enrollment of 2,734, and two schools were K-6, with a student enrollment of

361. In total, there were 131 classrooms with a total enrollment of 3,095 and about 120 teachers

and teaching assistants. Then, a ratio of a municipal student to city population is about one to

six.6 Besides municipal schooling, there were 15 schools and colleges operated by other agencies

(e.g., private, non-for-profit, regional schools and colleges, etc.) within the jurisdiction. Six are

K-6, three are K-9, five are 7–12, and two are community colleges, with a total student

enrollment of 16,157.

Where the number of city population in East Sea Beaches (the comparative case) is about five

times larger than that of the City of Tree Jasmine, East Sea Beaches just operated 11 schools in FY

2007. Seven schoolswereK-9, threewereK-12, and onewas secondary school,with total classrooms

of 304 and a student enrollment of 11,418. There were also 27 schools and colleges operated by other

agencies in East SeaBeaches that altogether provided schooling for about 27.8 thousandCity’s youth

population. Suffice it to say, the total educational supply in Tree Jasmine far outnumbered the city’s

youth population and, accordingly, the current communal demand for education.

It might also be possible that education spending boost in Tree Jasmine is resulting in

improved educational outcomes. Hence, higher education spending in this fiscally poor city is

justified. Notwithstanding, there is a lack of supportive evidence that municipal schools in Tree

Jasmine have done a good job in child schooling. Indeed, educational outcomes in Tree Jasmine

were relatively poorer than those of East Sea Beaches and those of the national average despite

the fact that the City government had spent massively on education in the past several years (see

Table 6). For instance the average year of schooling in Tree Jasmine was about 7.29 in 2007. By

TABLE 6

Average Education Outcomes of Municipal Schools, 2007 (2001)

City

Average Year

of schooling

General exam

average scores,

Grade 6

General exam

average scores,

Grade 9

Drop-out Rate

(Grades 6–9)

(%)

Tree Jasmine 7.29 36.05 (34.79) 36.85 (33.16) 6.0 (7.8)

East Sea Beaches 8.63 39.10 (38.94) 38.86 (35.05) 4.9 (5.5)

National Averages 7.68 38.33 (41.09) 37.53 (34.92) 3.5 (3.7)

Note: Numbers in parentheses are of 2001. General exam in Thailand incorporates math, science, reading, and social

science, all of which has a full score of 100.

Source: Department of Local Administration, Annual Statistics of Local Governments in FY 2007 and FY 2001 and the

Ministry of Education of Thailand.

6. Putting this ratio in comparison with that of the East Sea Beaches discussed above (which is about one to nine),

some form of abundant educational services in Tree Jasmine is clearly evident.


contrast, the figure of East Sea Beaches’ schools was about 8.63 years in the same year.

Additionally, the average general exam scores for Grades 6 and 9 in Tree Jasmine’s schools were

also slightly lower as compared with those of East Sea Beaches.

Thus, if educational spending in Tree Jasmine was not linked to service demands, the school

supply shortage, nor the need for better education outcomes, then mayoral policy preferences

behind municipal schooling tended to more aptly explain the existing educational spending

levels. This is where the role of priority setting and the politics of schooling steps into delineating

a more complete view of the political dynamics in Tree Jasmine. The next section explores the

political causes of expensive schooling. Suffice it to say that group politics and corporatism in

Tree Jasmine provided great venues for political opportunism.

Politics and Administration Behind the City’s Fiscal Condition. Rubin (1982) once argued that

political vulnerability inflates unnecessary spending and, thereby, diminishes the municipal

fiscal condition. Notwithstanding, the political vulnerability model has a restricted application to

the understanding of fiscal conditions in Tree Jasmine. The political base of the city mayor was

too secure. The mayor himself has governed the municipality since 2004 and was a Deputy

Mayor for about 13 years (from 1995 to 2003). Furthermore, councilmen had very close ties to

the mayor. Indeed they co-invested in several businesses.

Alternatively, the performance of budgetary checks-and-balance roles as developed by

Wildavsky (1975), later expanded by Schick (1988), Aarsaether (1990), and Good (2007), added

to this theoretical void. That is, the escalated education spending and the financial malpractices

attributed to the underperforming roles of the city’s key budget actors. Several instances

plausibly precipitated the budgetary roles’ collapse. Firstly, political priorities were set to fit the

personal needs of the key executives, who more or less had conflicts of interest with the

municipal government, rather than to fit urgent constituency needs. Secondly, the budget

guardian council was weakened by the strategies of the executives. Lastly, financial watchdogs

were not able to carry out their tasks due to an unsupportive working environment.

At a glance, it seemed politically reasonable that the City put education policy on top of its

priority list. While it was not the case earlier for Tree Jasmine, the coming of the new mayor in

2004 had brought about initiatives for having new schools. Why did other budget actors such as

councilors or auditors not say something against the school building spree? Both the former

Budget Director and the former Finance Director pointed out that spending on education and in

school-related items was a clever strategy that broke down the city’s check-and-balance system

and helped to serve other political ends. First, education spending was a basis for forging

political popularity in Tree Jasmine. Due to its semi-rural community, other competing programs

such as job training and the like had hardly been implemented successfully. Here, the good name

of education better solicited wide support in the constituency. At its simplest, its benefits were

more tangible to voters than job training programs.

Next, and most importantly, the Mayor himself secretly owned and ran several businesses

that seemed to have a conflict of interest with the municipal administration. That being said,

as the Director of City Planning stated, “most of the school construction contracts were

awarded to the Mayor’s own companies.” (Director of City Planning in Tree Jasmine,


personal interview with author, September 25, 2009) Under the budget category of education-

related constructions, they often mimicked “socially desirable” spending. When comparing

this with the construction of new roads, said the Director of Planning, “Almost no one really

criticized how many school buildings, libraries, or computer labs were newly constructed

each year. It was a clever, safer and quieter political tactic that helped divert public criticisms

from the construction of unneeded roads to public support under the good name of human

development programs.” (Director of City Planning in Tree Jasmine, personal interview with

author, September 25, 2009)

In the past, the construction of new school buildings and facilities was overwhelming. All of

the six municipal schools had excess physical capacity. For instance, in FY 2006, where this year

was the peak of school constructions in the past decade, seven buildings were newly constructed,

five were renovated, and five facilities (e.g., library, canteen, etc.) were newly constructed. All of

this construction cost the city 78.7 million Thai baht (about 2.3 million USD) or 61.7 percent of

the educational budget, whereas the budget left for teaching related activities was just 48.8

million baht or 38.3 percent. Note that the total investments for economic development were just

about 30.1 million baht in the same fiscal year.

That overall school capacity was over-supplied could be easily observed. On the one hand, the

biggest municipal school had a physical capacity to serve about 70 classes, whereas the current

enrollment was 40 classes. On the other hand, the smallest school had a capacity to educate

students for 10 classes or roughly 250–300 students. Yet, it actually served five classes with 157

enrolled students. Interviews with the City’s former Budget Director also corroborated this

observation. The director expressed that

“We had too many schools located nearby. Some of them were located within 1.1 kilometers

(or a 0.68 mile) radius from others. Several school buildings were left vacant. This was very

costly to the city especially in terms of administration, overhead costs and capital investment.

The better, more efficient strategy in managing school resources was to shut down about two

of the schools. We had to be vigilant in spending our taxpayers’ monies.” (Former Budget

Director of Tree Jasmine, personal interview with author, June 24, 2009)

Finally, several interest groups also accounted for having too many municipal schools.

Firstly, school principals and teachers were very powerful in Tree Jasmine. They helped to build

the good reputation of the Mayor and his team during political campaigns. Thus, one effective

way to please these influential groups and nurture political loyalty was to establish more, instead

of fewer, municipal schools. This is because, according to public choice theorists (e.g.,

Niskanen 1971; Daft 2007), a separate municipal school comes with autonomy, budget,

authority, and perhaps a greater chance of economic rent-seeking of related personnel.

Additionally, communal residents preferred having several small schools, rather than having a

few, large schools because having more schools meant more chances for residents to be

appointed as members of a school board. This was a sense of pride and social responsibility an

ordinary citizen could acquire.

One of the reform efforts in the past nine years included a proposed plan for school

consolidation, from six to four. The plan was co-initiated by the former Budget Director and the


Assistant Director to EducationDepartment of the Tree Jasmine and detailed that school closures

would not cause any serious transportation burdens for the majority of students due to school

proximity (two schools were located within 1.1 km or a 0.68mile radius from one to another) and

possibly help to reallocate school resources from excessive capital and overhead spending to

more focused teaching- and curriculum-development programs.

Notwithstanding, the consolidation plan failed to pass the policy window of city mayor

and councilors. Not only did the city mayor oppose the school consolidation idea, nor did it

secure any support from the city’s councilors, school board members, school principals, and

teachers. Indeed, school principals, and teachers of the schools to be shut down strongly

opposed the plan. Said an angry school principal, “That plan was ridiculous! My school was

everything to me. I started working from seven (a.m.) to six (p.m.). This school was indeed

my second home. I’d tried so hard to develop my school and to educate my students. In the

past, I fought for more budget or even asked for public donations so that my school could

provide students state-of-the-art, curriculum-related equipment and computers.” (School

Principal of a Tree Jasmine’s municipal school, personal interview with author, October 6,

2009)

In contrast with the Tree Jasmine’s experience in running schools just discussed, key budget

actors in East Sea Beaches kept their good eyes on administering municipal schools. They are

quite cautious when decision had to be made on a proposal to construct a new school in 2003.

While the number of municipal schools was steady at 10 during 1980s–1990s, rapid expansion of

the city in late 1990s had increased constituency demands for more schools. Eventually, a plan

for construction one new school wasmaterialized and got the legislative approval in 2003. In this

regard, the City Mayor of East Sea Beaches stated that:

“We worked very closely with the council as well as civic leaders and constituents. We

reviewed very carefully if the demands for new schools were in excess of our school supplies.

Having a clumsy bureaucracy was not our tradition. Civic leaders and councilors also shared a

similar view. All were so helpful in gathering views and comments from constituents in civic

forums and town-hall meetings. Finally we reached the joint decision in opening a new school

in 2003 and everybody had won.” (City Mayor of East Sea Beaches, personal interview with

author, November 13, 2009)

In addition to the corporatist and group politics of Tree Jasmine discussed above, the city’s

poor fiscal conditions also stemmed from the weakened guardian role performed by the Council.

It hardly questioned the policy priorities and budget allocation carried out by the executives.

“We saw that our role was to support the executive, not to block or challenge any initiatives of the

Mayor” (Secretary of Tree Jasmine City Council, personal interview with author, October 6,

2009), said the Secretary of the Council. Even worse, every councilman had to follow theMayor

in what priorities should be implemented in Tree Jasmine. This was because, elaborated the

former Budget Director, “those whowanted to run for Councilman had to get prior approval from

the Mayor. So, who would still dare to challenge mayoral power with respect to spending and

budgetary policy?” (Former Budget Director of Tree Jasmine, personal interview with author,

June 24, 2009)


Lastly, the financial watchdog role performed by the internal audit unit was not stringent and

indeed became weakened under the mayoral leadership. The City’s internal audit office was

understaffed, having one junior accountant who lacked auditing experience and four posts of

internal auditor were left vacant since 2002. Indeed, the Mayor did not want to expand the

capacity of the City’s internal audit team.

In short, that the City of Tree Jasmine was poor socioeconomically was partly a determinant

of the poor municipal fiscal condition. Indeed, the failure of the budgetary roles which was

evolved over time indicates a much more telling story of the fiscal conditions in Tree Jasmine.

Although bad socioeconomic luck made the City fiscally poor, its bad budgeting tended to

worsen the city finances. Weak budgetary control over the city finance and education spending

spree were indeed more of a product of the actors’ failures to conformwith their designated roles

than a product of external socioeconomic forces.

DISCUSSION AND POLICY RECOMMENDATIONS

The current research attempts to examine municipal fiscal conditions in Thailand during FY

2001 to FY 2006. The quantitative findings show that large, highly populous central cities as well

as semi-rural, residential areas were fiscally weak. By contrast, industry-based and suburban

cities were fiscally healthy. Later, two distinct cases are compared in order to explain how

perverted budgetary roles lay underneath the poor municipal fiscal conditions. Here, one

conclusion can be drawn: when a country becomes decentralized without definite assignments of

budgetary roles to key budget actors, a poor fiscal condition likely results. This is the

contribution of the budgetary roles theory to date where politicians and city administrators can

learn and should perform their designated roles within the context of fiscal decentralization,

especially for Thailand and other newly developed democracies.

A good learning case is East Sea Beaches. Although the City itself is socio-economically

better-off, its political executives as well as other respective budget actors work hard at keeping

the municipal purse in good shape. All budgetary roles seem adequately fulfilled. These include

the council’s guardianship role, the internal audit mechanisms and the external watchdogs such

as interest groups, local media and the OAG. By contrast, what cannot be commended is the case

of bad budgeting and the corporatism politics in Tree Jasmine. While city administrators attempt

to drain the fiscal resources through expensive educational spending, other financial safeguards

are not effective in that they could have assisted in making the municipal fiscal administration

more transparent and viable. Given these circumstances, the way to escape from the fiscal woes

for Tree Jasmine will require extensive political and administrative overhaul. Here are some

guidelines and recommendation on how improved budgetary roles of key budget actors assist in

improving municipal budgeting.

Firstly, an improvement in local politics and budgeting is highly necessary. One way to cure

the poor fiscal conditions of cities such as Tree Jasmine is to fortify the budgetary checks-and-

balance roles of budget actors at city hall. What is urgent is the strengthening of the council’s

roles in safeguarding the municipal purse and in examining the work of the executives, and the


Department of Local Administration (DoLA) could play a leading role in this regard. The DoLA,

as having a role of supervising municipal operations in Thailand, can issue policy guidance and/

or financial code of conduct on the proper budget guardian roles for municipal councilors and on

the policy advocate and financial watchdog roles for city administrators. This is a common

policy direction previously pursued by central agencies in several countries (ACIR 1962; Ladd

and Yinger 1989; Martinez-Vazquez and Boex 1997a, 1997b; White and Smoke 2005) and

Thailand can follow suit.

Secondly, a national monitoring system of local fiscal performances shall be developed and

put into use. To date, there has been significant development in the literature so that it can now

provide a more comprehensive and dependable view of local fiscal conditions (e.g., Kloha

et al. 2005; Wang et al. 2007). Notwithstanding, the DoLA is still passive in monitoring Thai

municipal fiscal performances. Clearly, the current research could be an input for the future

design of fiscal monitoring systems in Thailand and also elsewhere.

Auditing function is another area of concern, especially for poorly-managed municipalities.

Both internally and externally conducted audits are inadequate to deter wrongdoing or

suspicious fiscal activities. In this regard, strengtheningmunicipal fiscal governance and internal

audit capability can be put into local agendas. National agencies like the DoLA or the OAG could

step in to promote fiscal capacity building for the city government and the internal audit tasks.

Finally, the reform of the fiscal policy making process and the enhancement of group as well

as local media power are essential. Processes should become more transparent and adequately

engage all parties concerned. As the case studies have showed, participatory decision making

helped the City of East Sea Beaches effectually cut unnecessary old-age welfare provisions and

put a well thought out new-school construction plan. Through the wide-communication and

deliberative processes, excessive service requests will eventually be balanced out by those who

are more concerned with new tax increase schemes.

On the contrary, an opened, wide participatory process was not fully implemented in Tree

Jasmine as to key policy issues were only in the hands of the CityMayor, colluded councilors and

city administrators. This was true particularly when the school consolidation initiatives as

proposed by the city’s budget guardians were put on the shelf and no general public at the

grassroots ever had a chance to discuss their views on the school closure plan. For this reason, the

promotion of active citizenship and community engagement should be well in place. It could

help not only to form political priorities that nicely fit constituency needs but also to enhance the

financial prudence of municipal administration as a whole.

In sum, the good design of municipal budgetary functions in countries undergoing democratic

transformation is extremely essential and should be called upon. Underlying checks and balance

mechanisms reflect the significance of Wildavsky’s (1975) budgeting literature to date,

especially for developing societies where budget actors often lack definite views with regard to

their appropriate fiscal roles. Since the practice of Thai municipal finances is just beginning (so

do other newly decentralized nations), it is essential for policy makers and researchers alike to

develop an effectivemonitoring system ofmunicipal finance.Municipal fiscal condition analysis

is not just an academic exercise but also a subject of great interest to a variety of stakeholders.

Unless we examine the dynamics of municipal fiscal conditions and the practice of budgetary


roles, we can hardly know themagnitude and underlying causes ofmunicipal fiscal problems and

cannot go on to prescribe the right cure.

REFERENCES

Aarsaether, Nils. 1990. “Organizational and Spatial Determinants of Fiscal Stress: An Analysis of Norwegian

Municipalities.” Public Budgeting and Finance. 10 (1): 55–66.

Advisory Commission on Intergovernmental Relations [ACIR]. 1962. Measures of State and Local Fiscal

Capacity and Tax Effort. Washington D.C.: Government Printing Office.

———. 1988. State Fiscal Capacity and Effort. Washington D.C.: Government Printing Office.

Baltagi, Badi H. 1995. Econometric Analysis of Panel Data. New York, NY: John Wiley & Sons.

Bradbury, Katherine L. 1982. “Fiscal Distress in Large U.S. Cities.” New England Economic Review.

(January/February): 33–44.

Bradbury, Katherine L., Helen F. Ladd, Mark Perrault, Andrew Reschovsky, and John Yinger. 1984. “State

Aid to Offset Fiscal Disparities across Communities.” National Tax Journal. 37 (2): 151–170.

Daft, Richard L. 2007. Understanding the Theory and Design of Organization. Mason, OH: Thomson South-

Western.

Dye, Thomas R. 1984. “Government Finances in Declining Central Cities.” Publius: The Journal of

Federalism. 14 (2): 21–29.

Good, David A. 2007. The Politics of Public Money: Spenders, Guardians, Priority Setters, and Financial

Watchdogs inside the Canadian Government. Toronto: University of Toronto Press.

Halaby, Charles N. 2004. “Panel Models in Sociological Research: Theory into Practice.” Annual Review of

Sociology. 30: 507–544.

Kloha, Philip, Carol S. Weissert, and Robert Kleine. 2005. “Developing and Testing a Composite Model to

Predict Local Fiscal Distress.” Public Administration Review. 65 (3): 313–323.

Krueathep, Weerasak. 2010a. “Measuring Municipal Fiscal Health: The Application of U.S.-Based Measures

to the Context of Thailand.” International Journal of Public Administration. 33 (5): 223–239.

———. 2010b. “Bad Luck or Bad Budgeting: A Comparative Analysis of Municipal Fiscal Conditions in

Thailand.” Unpublished Ph.D. diss., Rutgers, The State University of New Jersey.

Ladd, Helen F. 1992. “Population Growth, Density, and the Costs of Providing Services.” Urban Studies. 29

(2): 273–295.

Ladd, Helen F. and JohnYinger. 1989.America’s Ailing Cities: Fiscal Health and the Design of Urban Policy.

Baltimore, MD: Johns Hopkins University Press.

Martinez-Vazquez, Jorge and L. F. Jameson Boex. 1997a. “Fiscal Capacity: An Overview of Concepts and

Measurement Issues and Their Applicability in the Russian Federation.” Working Paper 97-3 (June):

Policy Research Center, Andrew Young School of Policy Studies: Georgia State University.

———. 1997b. “An Analysis of Alternative Measures of Fiscal Capacity for Regions of the Russian

Federation.” Working Paper 97-4 (June): Policy Research Center, Andrew Young School of Policy

Studies: Georgia State University.

Ministry of Finance of Thailand. 2012. Annual National Statistics of Thailand. Bangkok: Government

Printing House (in Thai).

Nielsen, Francois and Arthur S. Alderson. 1995. “Income Inequality, Development, and Dualism: Results

from an Unbalanced Cross-National Panel.” American Sociological Review. 60 (5): 674–701.

Niskanen, William A. 1971. Bureaucracy and Representative Government. Chicago, IL: Rand McNally.

Olowu, Dele and Paul Smoke. 1992. “Determinants of Success in African Local Governments: AnOverview.”

Public Administration and Development. 12 (1): 1–17.

Patmasiriwat, Direk. 2006. Local Finance: Collected Research Papers. Bangkok, Thailand: P.A. Living Press

(in Thai).


Rafuse, Robert W. 1990. Representative Expenditures: Addressing the Neglected Dimension of Fiscal

Capacity. Washington D.C.: U.S. Advisory Commission on Intergovernmental Relations.

Rodden, Jonathan A. 2002. “The Dilemma of Fiscal Federalism: Grants and Fiscal Performance around the

World.” American Journal of Political Science. 46 (3): 670–687.

Rodden, JonathanA. 2006.Hamilton’s Paradox: The Promise and Peril of Fiscal Federalism. NewYork, NY:

Cambridge University Press.

Rubin, Irene S. 1982. Running in the Red: The Political Dynamics of Urban Fiscal Stress. Albany, NY: State

University of New York Press.

Schick, Allen. 1988. “An Inquiry into the Possibility of a Budgetary Theory.” In New Directions in Budget

History, edited by Irene S. Rubin, 59–69. Albany, NY: State University of New York Press.

Suwanmala, Charas. 2001. The Development of Local Financial Management. Final Report to the Office of

National Economic and Social Development Board (NESDB). (in Thai).

Varanyuwatana, Sakon. 2003. “Thailand.” In Local Government Finance and Bond Markets, edited by Yun

Hwan Kim, 525–566. Manila, Philippines: Asian Development Bank.

Wang, Xiaohu, Lynda Dennis, and Yuan Sen Tu. 2007. “Measuring Financial Condition: A Study of U.S.

States.” Public Budgeting and Finance. 27 (2): 1–21.

Warner, Mildred E. and Amir Hefetz. 2002. “The Uneven Distribution ofMarket Solutions for Public Goods.”

Journal of Urban Affairs. 24 (4): 445–459.

Wasylenko, Michael and John Yinger. 1988. Nebraska Comprehensive Study, Final Report. Metropolitan

Studies Program, the Maxwell School, Syracuse University, Syracuse, New York (July).

Wildavsky, Aaron. 1975. Budgeting: A Comparative Theory of Budgetary Process. Boston, MA: Little,

Brown and Company.

Wildavksy, Aaron. 1984. The Politics of Budgetary Process. Boston, MA: Little, Brown and Company.

White, Roland and Paul Smoke. 2005. “East Asia Decentralizes.” In East Asia Decentralizes: Making Local

Government Work, International Bank for Reconstruction and Development, 1–24. Washington D.C.:

The World Bank.

Wooldridge, Jeffrey M. 2000. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-

Western College Publishing.

Zafra-Gomez, Jose L., Antonio M. Lopez-Hernandez, and Agustin Hernandez-Bastida. 2009. “Evaluating

Financial Performance in Local Government: Maximizing the Benchmarking Value.” International

Review of Administrative Sciences. 75 (1): 151–167.

APPENDIX A

Following the framework developed by Martinez-Vazquez and Boex (1997a, 1997b) and Dye

(1984), municipal revenue-raising capacity (RRC) will be estimated from

RRCi ¼ f ðeconomicwealth; demography; economic developmentÞ ð2Þ

where RRCi is revenue-raising capacity for each of the ith taxes/revenues. Here, the major

determinant of taxing capacity consists of city economic wealth, demography and city economic

development. Wealth includes gross city product per capita, property wealth, and city areas

(km2); demography includes population density (per km2) and population growth rate; and the


level of economic development includes the cost of living as measured by the consumer price

index, the proportion of the labor population to the total city population and a dummy for the

economically concentrated area. These variables are included, with respect to data availability,

as suggested by the literature (e.g., Wasylenko and Yinger 1988).

On the other hand, the estimation of expenditure need (EN) as developed by Ladd and Yinger

(1989) is derived from

ENi ¼X

j½Qj � Sij � Cij� ð3Þ

where

i¼ city ith from 1, 2, …, N

j¼ expenditure function jth from 1, 2, …, n

Qj¼ standardized per capita spending on the jth expenditure function

Sij¼ the ith city’s index of service responsibility for the jth spending function relative to the

average of all cities

Cij¼ cost factors, which are ith city’s index of per capita costs for the jth spending program

relative to the average over all cities

Then, cost factors (or cost indices) are estimated from

Ci ¼ EXPPCSIMi=EXPPCi ð4Þ

and

EXPPCSIMi ¼ gðDEMANDa;AIDa;PREFa;COSTFACTORiÞ ð5Þ

EXPPCi ¼ hðDEMANDi; AIDi; PREFi; COSTFACTORiÞ ð6Þ

The estimated EN represents the potential spending level for each of the service functions,

given average service quality (as reflected in Qj in equation (3)) and the scope of service

responsibilities (as reflected in Sij in equation (3)). Service responsibility indices (Sij) are

calculated from the proportion of spending in each program of the average city. In this study,

indices for public education¼ 0.3, housing and community services¼ 0.35, public safety¼0.05, public health¼ 0.05, social welfare¼ 0.05, and general administration¼ 0.2. According to

Ladd and Yinger (1989), the indices were estimated from proportions of municipal spending of

the sampled cities for each of the service programs.

A city’s variation in the EN occurs when its cost index is higher or lower than other

comparable cities (as captured by Ci in equation (4)), whereas a is the average value of the

studied cities and i is the value of ith city. EXPPCSIM is the predicted value of per capita

spending given the average levels of determining factors for spending, demand, intergovern-


mental aid and citizen preferences but given the city’s values of cost factors. EXPPC is the

predicted value of per capita spending given the data of each respective city.

Statistical estimations for the RRC and the EN were carried out by a random effect (RE)

estimator for each of the five revenue sources and six spending programs.7 Then, they were

added together in order to obtain the overall RRC and the overall EN. On the whole, the

regression models did reasonably well in predicting the RRC and the EN (R2(between) were

between 0.625 and 0.981, with p-values <0.001 for all models). Because of limited space, full

regression results are not shown but are available from the author upon request.

7. Generally, the analysis of fiscal conditions examines fiscal strengths across the cities (between-city variations).

The RE estimator recognized the heterogeneity of local fiscal conditions across cities induced by city-specific,

unobservable effects (Nielsen and Alderson 1995; Wooldridge 2000; Halaby 2004). By contrast, using fixed effect

(FE) estimators would throw away any between-unit variations. Thus, the RE estimator is preferable. It is also

reasonable to assume that unobservable, city-specific effects are exogenous of other explanatory variables. For

instance, unobservable factors might be local political culture that is not necessarily correlated with local

socioeconomic factors. Hence, the basic assumptions of the RE are not violated. That is, RE is still BLUE (best linear

unbiased estimator) under the assumption that E(uit|Xit)¼ 0 (Baltagi 1995). Finally, a Hausman Test between the FE

and RE estimators indicates that, for most of the regression models (10 out of 11), it fails to reject the null hypothesis

at 95 percent confidence level, meaning that there is no evidence to argue that the FE estimator provides better results

than the RE.


bad luck or bad budgeting: an analysis of budgetary roles underpinning poor municipal fiscal...

Documents