Oana Mihaescu, Niklas Elert, Hans Seerar Westerberg (p)

Anders Bornhäll

Crime is generally assumed to bring significant costs to both the affected individual and society, and the risk of being exposed to crime is argued to cause consumers, workers, and entrepreneurs to change their behavior and operations. Some studies find that the costs of crime for businesses are significant, however other studies argue that there is no clear consensus on the effect of crime on business activity.

To examine the consequences of crime for local business activity we plan to measure the effects of an exogenous shift, namely the implementation of collaborative place-based programs to deter crime. The Swedish National Board of Health and Welfare defines such programs as “comprehensive joint actions at the organizational level for a specific purpose”, which “can occur within and between, for example, units, authorities, and community actors and can involve active exchange of information or planning of joint activities”.

Clarifying whether collaboration programs work and what their effects are is important for future policy-making. In this paper we evaluate the effects of three such programs: BID Sofielund implemented in Malmö in 2014, a Swedish program for focused deterrence called “Stop Shooting”, as well as another type of collaboration program called Effective Coordination for Safety (EST). To identify the effects of these collaboration programs on the performance of the businesses in the areas where they have been implemented, we use the programs as a natural experiment in combination with a regression model based on a difference-in-difference (DiD) approach. To measure business performance, we use an unbalanced micropanel dataset that includes the key figures for all limited-liability companies in Sweden. We then use a DiD methodology to compare the outcomes of businesses in areas where the programs have been implemented with the outcomes of the same businesses, before the implementation time point, and with a group of control businesses. The analysis covers the period 2010 – 2022.

Preliminary results indicate that, while such programs seem to have no effect on the revenues of the firms in the treated areas, there is a significant negative effect on employment. This result could be linked to a series of factors such as stricter regulations and even gentrification processes. From a practitioners’ perspective, it is important to clarify this relationship, because the general understanding and expectation is that reducing crime will inevitably create a more economically prosperous area.

Anders Bornhäll, Oana Mihaescu (p), Olga Lark

Viktorija Baranauskiene

Access to essential commercial services, such as food retailers, is a cornerstone of rural community sustainability. However, since the mid-1990s, food retailers in Sweden's remote areas have steadily declined. This trend has worsened in recent years, particularly due to the COVID-19 pandemic, which led to further closures and operational struggles among rural retailers. Beyond providing food, these retailers serve as key service hubs, offering postal services, pharmacy products, and fostering community engagement. To counteract this decline, the Swedish government introduced a financial support program in 2016, allocating 35 million SEK annually, later expanded to 70 million SEK in 2018 to include more businesses. However, the effectiveness of this support remains widely debated.
This study evaluates whether the government’s support package has successfully mitigated the negative trend in rural grocery retail. Specifically, we investigate (1) whether the decline in store performance has been reversed, (2) the extent to which the support has contributed to store survival, (3) its impact on key financial and operational metrics such as turnover, employment, productivity, profits, and operating margins, (4) differences in outcomes between the original support recipients and those included in the 2018 expansion, and (5) how stores have allocated the support, e.g., toward wages, employment, or other business improvements.
Our analysis employs a quantitative approach using administrative data on rural grocery stores, comparing financial and operational performance before and after the support program’s implementation. Preliminary results suggest a modest positive effect on sales and employment, though no statistically significant impact on store survival was found. However, recipients significantly increased wage payments, suggesting a potential link to extended opening hours. The 2018 expansion recipients saw similar but less pronounced effects. By analyzing the impact of financial aid on store performance and survival, this study contributes to the ongoing debate on the effectiveness of public intervention in sustaining rural commercial services. The findings will inform discussions on whether the current support model should be revised or expanded to better address the evolving needs of small retailers and promote long-term growth.

Viktorija Baranauskiene (p), Jurga Bucaite-Vilke , Aiste Lazauskiene, Ieva Dryzaite

Khoirunurrofik Khoirunurrofik

The most recent elections for municipal councils and mayors in Lithuania took place on 5 March 2023. This election is exceptional because the new provisions of the Law on Local Self-Government of the Republic of Lithuania have changed the institutional set-up of the municipality. The powers of mayors are separated from those of councillors (the mayor has become the executive and has more powers). Therefore, with the reform of the institutional structure of municipalities, it is important to better understand how local leadership processes are being reshaped and how the conditions for citizens' participation in local democracy are changing, as local government faces many challenges in decision-making: understanding its role, the importance and impact of decisions, the cooperation and representation of local citizens and businesses and their involvement in decision-making and problem-solving, and so on. The aim of this report is to reveal the spatial distribution of the newly elected Lithuanian municipal councillors' attitudes towards the prioritisation of the local government agenda in the country. To achieve the aim of the thesis, quantitative (questionnaire survey) and qualitative (interviews) data were used. The quantitative data is derived from the European councilor questionnaire survey (for the purposes of this report, only the case of Lithuania is presented (the survey was carried out between February and March 2024)). All 1,498 municipal councillors from 60 municipalities were surveyed and 694 questionnaires were received. 24 interviews were conducted in three municipalities in Western Lithuania: Klaipeda city, Klaipeda district and Kretinga district, corresponding to urban, suburban and periphery cases. The data analysis revealed that the preferences of municipal councillors on the prioritisation of agenda items are unevenly distributed across the country. Different regions of the country have different problems, with clear differences between urban (centre) and rural (periphery) municipalities. Policy-makers in the country's peripheral regions are mainly concerned with specific local issues, while those in the cities are more concerned with global issues. The questionnaire survey data were processed using IBM SPSS Statistics and ArcGIS Pro software, and the interviews were analysed using MAXQDA software.
This research was funded by a grant („Changing role of local councilor in self-governance: leadership, institutions and communities“, Nr. S-MIP-23-17) from the Research Council of Lithuania.

Khoirunurrofik (p), Arief, S. Gusnanto, Bagus Sartono, Arthur H. Bramantyo, Ali Kifayatullah

Oana Mihaescu

The relationship between political factors and corrupt behaviour, including the way in which leaders and legislators interact in the budgetary decision-making process, has led to many local governments in Indonesia being implicated in corruption cases. This study uses artificial intelligence/machine learning (AI/ML) methods to predict corrupt behaviour based on local political competition, fiscal policy, and economic structure that proposes a new approach to predicting the corrupt behaviour of local governments in Indonesia. We used random forest and gradient boosting algorithms, which are considered the best approaches to artificial intelligence for predicting. Data for corruption cases are provided by the Corruption Eradication Commission (Indonesia: Komisi Pemberantasan Korupsi) and Indonesian Corruption Watch, in particular for cases under investigation by the Regional Prosecutor's Office and the State Prosecutor's Office. The political configuration data is collected by the Ministry of Home Affairs and the General Election Committee. The tax data is collected by the Ministry of Finance, while the economic and geographical data comes from Central Beureu Statistics. From a fiscal point of view, corrupt behaviour also affects the planning budget, as it leads to a budget deficit, a higher share of social assistance and a high share of infrastructure spending. The study found that public expenditure, education expenditure and poverty levels are important predictors of corruption cases. The presence of lag variables, such as education expenditure in the past, suggests that past patterns of expenditure play a significant role in determining the level of susceptibility to corruption in the present. This observation provides an insight that, in addition to focusing on current expenditure, it is also important to assess past expenditure trends in order to understand patterns of recurrent corruption risk. An analysis of the predictability of corrupt behavior in Indonesian local governments could provide an alternative early warning system for the design of government financial policies that can reduce corruption. Lessons learned from major developing countries with big decentralisation reforms will contribute to building a body of knowledge about local public finances and regional academic studies.