Pakistan Economic and Social Review Volume 47, No. 1 (Summer 2009), pp. 79-98



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GILLANI et al.: Unemployment, Poverty, Inflation and Crime Nexus

Pakistan Economic and Social Review
Volume 47, No. 1 (Summer 2009), pp. 79-98

UNEMPLOYMENT, POVERTY, INFLATION AND
CRIME NEXUS: COINTEGRATION AND
CAUSALITY ANALYSIS OF PAKISTAN

SYED YASIR MAHMOOD GILLANI
HAFEEZ UR REHMAN and ABID RASHEED GILL*


Abstract. This study is designed to investigate the relationship between crime and various economic indicators such as unemployment, poverty and inflation in Pakistan. The study covers the period for 1975-2007. The stationary properties of the time series data are examined by using Augmented Dickey-Fuller (ADF) test. Johansen Maximum Likelihood Cointegration and Granger Causality tests are applied to find out long-run relationship along with causality among the variables. The findings of the tests provide evidence of the existence of long-run cointegration relationship among crime, unemployment, poverty and inflation. The Granger causality has been tested through Toda-Yamamoto procedure. The causality results show that crime is Granger caused by unemployment, poverty and inflation in Pakistan.
I. INTRODUCTION

Crimes have always plagued every society in human history. The history of crime is as old as history of mankind. The first crime was committed by Cain, the first son of Adam and Eve, when he murdered his brother Abel out of jealousy.

Crime is a major source of insecurity and discomfort in every society. There is no doubt that crime inflicts enormous monetary and psychological costs on society. The act of criminality gives rise to the feeling of insecurity and fear to those who have not been a victim as well. This sense of panic of being victimized generates negative effects on well being.

Crime can be defined as a wrongdoing classified by the state or the parliament of the country or law of the land. Each country sets out series of acts (crime), which are prohibited, and punishes a criminal of these acts by a fine or imprisonment or both.

There is no universal and permanent definition of crime. It differs in different times in different regions. According to Curzen, “A crime as an act or omission of human conduct harmful to others which the state is bound to prevent. It renders the deviant person liable to punishment as a result of proceedings initiated by the state organs assigned to ascertain the nature, the extent and the legal consequences of that person’s wrongness” (see Auolak, 1999).

The literature on Economics of Crime sprang from the seminal contribution by Becker (1968) and Ehrlich (1973). In 1968, Becker presented a paper which changed the way of thinking about criminal behaviour. He was the one who built first model of criminal choice stressing that “some individuals become criminals because of the financial and other rewards from crime compared to legal work, taking account of the likelihood of apprehension and conviction, and the severity of punishment.”

The Becker’s paper opened the door to a new field of empirical research whose main purpose was to verify and study the socioeconomic variables that affect crime. The economics of crime interacts with different and heterogeneous fields, i.e. (Sociology, Criminology, Psychology, Geography and Demography) and it is closely related to poverty, social exclusion, wage and income inequality, cultural and family background, level of education and other economic and socio-demographic factors that may affect an individual’s propensity to commit crime such as age, gender and urbanization.

Economics of crime has become a new field of investigation, particularly due to the fact that there has been a rapid increase in criminal activities in various western and eastern countries of the world. There is a vast amount of literature available on the relationship between crime and their major determinants in countries like United States, United Kingdom, Germany and Italy. Some studies are also conducted which have analyzed the determinants of crime in Latin American countries such as Colombia and Argentina, e.g. Buohanno (2003).

No in-depth and systematic study of the impact of lawlessness on Pakistan’s economy has been undertaken so far. Stray articles have appeared in newspapers and magazines highlighting the adverse impact of disturbances but the problem has not been examined in any coherent way from the standpoint of national economy as a whole. This study is an attempt to identify and examine the economic factors responsible for promoting crime in Pakistan. The main objective of the study is to analyze empirically the relationship between crime and major economic factors (unemployment, poverty and inflation) and to recommend policy measures to help check and prevent crime rate in Pakistan.

The remainder of the paper is organized as follows. In section II, relevant literature is reviewed. Section III presents crime scene in Pakistan. Methodology is discussed in section IV. The results of the study are elaborated in section V. Conclusions are presented in section VI and finally section VII presents proposed suggestions.

II. REVIEW OF PREVIOUS STUDIES

Many studies have been conducted on the relationship between crime and its determinants. The results of these studies show that these various factors are responsible for promoting crime in the world.

Fleisher (1966) studied the role of income on the decision to commit criminal acts by individuals. The author stated that the principal theoretical reason for believing that low income increases the tendency to commit crime is that the probable cost of getting caught is relatively low. It is because of the reason that low income individuals view their legitimate lifetime earning prospects dismally they may expect to lose relatively little earning potential by acquiring criminal records. They feel that not only legitimate earnings are ‘low’ but also the opportunity cost of time actually spent in delinquent activity, or in jail, is low.

Becker (1968) presented a model based on costs and benefits. His approach was formed from the usual analysis of the expected utility; that persons will commit crime or offence if they presume that their utility will be greater than if they used their time and resources in some other activity.

Ehrlich (1973) considers that unemployment has its effects on crime rate. He says that unemployment rate can be viewed as a complementary indicator of income opportunities available in the legal labour market. Therefore, when unemployment rate increases, the opportunities in the legal sector decrease leading individuals to involve in criminal activities.

Fajnzylber et al. (2002) using simple correlations, OLS regressions and dynamic Generalized Method of Moments (GMM) for panel data show that both income inequality and crime rate are positively related.

Lee (2002) examines the relationship between labour market conditions and various crime series in three Asia-Pacific countries, Australia, Japan and South Korea. Johansen maximum likelihood cointegration and Granger causality tests were applied to time series data to see the existence of long-run equilibrium or a causal link between unemployment and crime variables. The results of the study provide a strong support for a long-run equilibrium relationship between unemployment and various crime series.

Coomer Nicole (2003) undertook a study to examine the influence of macroeconomic factors on crime. He applied OLS regression to find out the results. In his analysis, he first included unemployment, poverty, prison population, high school and college education level and income disparities as independent variables and run the regression to get the relationship. He then dropped the insignificant variables and rerun the regression and found that unemployment, inflation and poverty influence crime positively.

Gumus (2004) uses large US city data to empirically investigate the determinants of crime in urban areas using OLS regression technique. The results indicate that income inequality, per capita income, and presence of black population are all important determinants of crime in urban areas. Unemployment rate and police expenditures have also important effect in the determination of crime.

Teles (2004) investigates the effects of macroeconomic policies on crime. He points out that monetary and fiscal policies have an impact on crime. His results show that fiscal policies affect crime through government spending and monetary policy affects crime through inflation.

III. CRIME SCENE IN PAKISTAN

PAKISTAN STATUS IN THE WORLD OF CRIME


To start with this section, we shall have a look at the crime picture in the world as well as in Pakistan. Table 1 provides the total number of crime of the world top countries along with other selected countries including Pakistan.

Table 1 shows that the United States, Germany and United Kingdom are the top three countries in absolute numbers. Pakistan’s rank is 23rd amongst other countries whereas India is 10th. Daily average of crime in Pakistan is 1144 as against 64870 in USA, 17164 in Germany, 14166 in UK and 4834 in India.

TABLE 1
Total Crime by Country

Rank

Country

Total Crime

Rank

Country

Total Crime

1

United States

23677800

10

India

1764630

2

Germany

6264720

19

Finland

530270

3

United Kingdom

5170830

20

Denmark

504240

4

France

3771850

22

New Zealand

427230

5

South Africa

3422740

23

Pakistan

417846*

6

Russia

2952370

37

Greece

102783

7

Canada

2476520

40

Ireland

81274

8

Japan

2443470

50

Moldova

38267

9

Italy

2205780



Pakistan

538048**

*1999 Figure, **2007 Figure

Source: Seventh United Nations Survey of Crime Trends and Operations of Criminal Justice Systems (United Nations Office on Drugs and Crime, Centre for International Crime Prevention), Bureau of Police Research and Development, Ministry of Interior, Islamabad.




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