Poverty & Inequality

Crime in the village: Does road infrastructure make a difference?

  • Blog Post Date 22 December, 2021
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Shreya Biswas

BITS Pilani, Hyderabad Campus


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Ritika Jain

Centre for Development Studies


Access to better infrastructure is critical for poverty alleviation and economic development in rural India. Analysing data from the 2004-05 and 2011-12 waves of the India Human Development Survey (IHDS), this article shows that households in villages connected with pucca roads had better outcomes in terms of crime, labour force participation, and family income, relative to those residing in villages with no pucca roads.

Road infrastructure is essential for growth and economic development, especially in developing economies. Despite experiencing high economic growth in the early 2000s, India has been grappling with a weak and inadequate infrastructure network. While necessary for urban areas as well, access to better infrastructure is critical for poverty alleviation and economic development in the rural sector. Within the infrastructure sector, roads have been at the forefront of economic development in India, with rural road development plans receiving attention since independence. Yet, lack of planning, improper design, and poor monitoring, has led to several deficiencies in the rural road network (Samanta 2015). Inadequate embankment and poor drainage networks has implied that most of these roads are not accessible during rough weather.

Against this backdrop, a centrally sponsored scheme, Pradhan Mantri Gram Sadak Yojana (PMGSY), was launched in 2000. The scheme's primary objective was to provide rural habitations1 with an all-weather pucca road within 500 metres of the habitation. While it was a scheme introduced by the central government, state and local governments were actively involved in the implementation of the project. PMGSY was implemented according to population criteria in a phased manner – villages that had a population of 1,000 or more were prioritised in the first phase (with a few exceptions2), the second phase included villages with a population of 500, and the third (and final) phase included villages with a population of 250. However, in 2010 the scheme was opened to all villages. Additionally, the roads being built were to be connected with the core network of roads within the state.

In 1951, a mere 20% of Indian villages had access to an all-weather road, and this increased to 60% in 2000 (Ministry of Rural Development, 2011, Lei et al. 2019). As of 2019, the access has spread to 73% of Indian villages. A few studies have specifically analysed the effect of transportation networks on economic outcomes in India. Ghani et al. (2016) found that the Golden Quadrilateral (GQ) – a highway construction and improvement project in India – improved the manufacturing output in districts close to the highway. In another study, Lei et al. (2019) documented that road access is related to improved employment outcomes for individuals, with a stronger effect observed for women. In recent research (Jain and Biswas 2021), we explore another important but less studied dimension of the transport network, that is, how road infrastructure correlates with criminal activities in rural India.

Road infrastructure as a determinant of crime

Individuals tend to become more risk-averse when facing significant changes in their external environment, such as a natural calamity, civil unrest, a pandemic, or violent crime (Brown et al. 2019). A crime-induced rise in risk aversion has adverse implications on human development by restricting mobility and reducing access to employment and education opportunities (Dutta and Hussain 2009). Further, due to informal markets, weak institutions, and poor quality of infrastructure, the probability of being caught and convicted of a crime are lower in developing countries than the developed ones (Bennett 1991, Chatterjee and Ray 2014). Becker (1986) pioneered the ‘economics of crime’, and suggested that criminals were rational agents deciding whether to indulge in criminal practices based on their benefits and costs. Following Becker (1986), a large body of literature has explored the determinants of crime. These studies identify several factors that contribute to higher crime rates, such as unemployment, extent of urbanisation, presence of immigrants, previous incidence of crime, and quality of institutions. On the other hand, the sociological literature has focussed on how the social theory of relative deprivation may be one of the significant determinants of crime. This theory posits that more impoverished and unequal societies have higher crime rates due to people feeling deprived, relative to their peers.

Besides these socioeconomic factors, road infrastructure may also influence crime rates (Hughes 1998). There are two channels through which roads may influence crime. First, local development through roads may lead to better employment opportunities. Revisiting Becker's (1968) model suggests that the opportunity cost of crime rises with better employment opportunities. As a result, individuals may substitute time spent on crime with employment. Hence, Becker's (1968) framework implies that building road infrastructure should impede and deter crime. However, if the economic benefits of employment due to roads disproportionately favour skilled and endowed individuals, those who are unskilled may still partake in criminal activities. In contexts where the group that would benefit from better road infrastructure forms a minuscule share of the population, road infrastructure may result in a rise in criminal activity through a rise in inequality.

Another channel that determines how road infrastructure may influence crime stems from the implementation of infrastructure development itself. Roads reduce time costs and increase mobility – critical for both criminal and economic activities. A well-connected road network may catalyse the movement of criminals to potential hotspots with ease.

Against this background, we seek to examine how building road infrastructure influences crime in rural India.

Data on crime in India

There are two possible ways to gather information on criminal activities in India – crime records maintained by the concerned nodal agency, that is, the NCRB (National Crime Records Bureau) and information collected from victims directly through a survey. The former source of information passes through several intermediary agents between the crime scene and the nodal agency. Further, Using police records of crimes from NCRB may have several limitations in capturing the actual pattern of crime, since various crimes in India go unreported due to poor infrastructure, weak institutions, and social stigma. In fact, the under-reporting of crime is a global issue – according to International Crime Victim Survey data, only 40% of committed crimes are reported at the global level. However, under-reporting of crime is more pervasive in developing economies. The study also documents that while the trend of violent crimes, such as murders, in India is not very different from the developed world, other criminal activities such as burglary and theft have a higher likelihood of not being reported3. Further, underreporting of crime in India, is a consequence of victims choosing not to report, and also the police deciding not to record it (Ansari et al. 2015). While police records are a valuable source of information, using victim-reported crime may reduce the scale of underestimation. Such data are gathered from surveys directly, by asking respondents if they faced any crime in the past year.

Road infrastructure and crime

We use data from the India Human Development Survey (IHDS) conducted in two waves – 2004-05 and 2011-12. The IHDS has four questions on whether households faced instances of burglary, threats or attacks, female harassment, and someone breaking into their home. Based on these criminal activities, we construct two measures of crime: (i) A simple average of each of the four types of crime, and (ii) A dummy variable that takes a unit value if anyone in the household is a victim of either of the four types of crime and zero otherwise.

Both waves of IHDS also have a separate questionnaire for village-level amenities, population composition, and occupation structure, among other attributes. Using information from the village questionnaire on whether the village was accessible through an all-weather pucca road or kaccha road, or was inaccessible, we construct our focal variable – the presence of a pucca road in the village. We also consider village- and household-level factors that may influence crime.

We measure aggregate patterns between road infrastructure and crime by focussing on how various economic outcomes differ between villages with pucca roads and villages without them. We compile the results in Table 1.

Table 1. Mean/average difference according to road infrastructure in the village


Pucca roads

No pucca roads


Types of criminal activity

Crime index 1




Crime index 2
















Breaking into home




Other facilities and economic outcomes





Bus stop distance




Employment ratio




Household income




Notes: (i) p-value is the probability of getting results at least as extreme as the results observed, given the assumption that the null hypothesis is true. A p-value lower than a mentioned significance level would be considered statistically significant (if p < 0.01, it is statistically significant at the 1% level). * p < .05, ** p < .01, ***p < .001 (two-sided).

Table 2 suggests that most crime measures are lower for households dwelling in villages with an all-weather pucca road than households that reside in villages without it. Further, we find that villages with pucca roads also have a higher probability of getting streetlights through a public programme. Similarly, this group of villages also has a bus stop that is closer to the village than the group of villages that do not have a pucca road. Finally, families dwelling in villages with well-connected roads exhibit better labour force participation rates and higher family income. These patterns indicate that rural road infrastructure may be effective in tackling crime in India.

Discussion and policy implications

Our preliminary observations highlight the importance of building a solid infrastructure base in developing economies. In addition to improving employment opportunities, road infrastructure generates positive spillover effects in the form of reduced crime. This has significant policy implications in designing and implementing policies that focus on investing resources in these projects despite long gestation periods. The ongoing Covid-19 pandemic has deepened the existing inequality of income, gender, and caste in India (Deaton 2021, Deshpande 2021, World Bank, 2020). Under these circumstances, the role of the government in scaling up investment in infrastructure projects like roads becomes pivotal to ensure that the pandemic-induced rise in inequality is short-lived thus leading to reduced criminal activities.

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  1. Rural habitation is defined as a cluster of the population that resides at the same location along the lines of a hamlet.
  2. For instance, if a habitation with less than 1,000 population lay on the straight path of a road that was built for a habitation with higher than 1,000, it was included in phase 1.
  3. This is based on data from two rounds of the International Crime Victim Survey in 1992 and 2003 in which select Indian cities were included. For more details, see Ansari et al. (2015).

Further Reading

  • Ansari, Sami, Arvind Verma and Kamran M Dadkhah (2015), “Crime rates in India: A trend analysis”, International Criminal Justice Review, 25(4): 318-336.
  • Becker, GS (1968), ‘Crime and punishment: An economic approach’, in GS Becker and WM Landes (eds.), The Economic Dimensions of Crime.
  • Bennett, Richard R (1991), “Development and Crime: A Cross-National, Time-Series Analysis of Competing Models”, Sociological Quarterly, 32(3): 343-363.
  • Brown, Ryan, Veronica Montalva, Duncan Thomas and Andrea Velásquez (2019), “Impact of violent crime on risk aversion: Evidence from the Mexican drug war”, Review of Economics and Statistics, 101(5): 892-904.
  • Chatterjee, Ishita and Ranjan Ray (2014) “Crime, corruption and the role of institutions”, Indian Growth and Development Review, 7(1): 73-95.
  • Deaton, A (2021), ‘Covid-19 and global income inequality’, NBER Working Paper No. 28392.
  • Deshpande, Ashwini (2021), “How India's Caste Inequality Has Persisted—and Deepened in the Pandemic”, Current History, 120(825): 127-132.
  • Dutta, M and Z Husain (2009), ‘Determinants of crime rates: Crime Deterrence and Growth in post-liberalized India’, Working Paper.
  • Ghani, Ejaz, Arti Grover Goswami and William R Kerr (2016), “Highway to Success: The Impact of the Golden Quadrilateral Project for the Location and Performance of Indian Manufacturing”, Economic Journal, 126(591): 317-357.
  • Hughes, David W (1996), “The Effects of Infrastructure Development on Crime in Rural Areas: A Case Study of the A55 Coastal Expressway in North Wales”, Cambrian Law Review, 27(33).
  • Jain, R and S Biswas (2021), ‘The road to safety- Examining the nexus between road infrastructure and crime in rural India’, arXiv:2112.07314.
  • Lei, Lei, Sonalde Desai and Reeve Vanneman (2019), “The impact of transportation infrastructure on women's employment in India”, Feminist Economics, 25(4): 94-125.
  • Ministry of Rural Development (2011), ‘Working Group on Rural Roads in the 12th Five Year Plan’, Report.
  • Samanta, Pradeepta Kumar (2015), “Development of rural road infrastructure in India”, Pacific Business Review International, 7(11): 86-93.
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