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ABSTRACT Objective: state capacity constitutes the set of essential competences that government institutions have (or should have) in order to achieve public objectives. However, the multidimensional nature of the ‘state capacity’ construct implies a major research challenge for the scientific academy and a major management challenge for public managers. Theoretical framework: the creation of State Capacity Index (SCI) follows the same procedures as the Human Development Index (HDI). Method: the search for variables (proxies) that are pertinent to the Brazilian context and that empirically allow the measurement and operationalization of state capacity was carried out through extensive bibliographic research. Therefore, SCI allowed the general examination of the ‘state capacity’ construct. Results: the results are disparities in the municipal administrative structures of Minas Gerais. Conclusion: it is suggested the need for incentives and investments in the dimensions that cover the State Capacity Index, namely: administrative, political, and fiscal. RESUMO Objetivo: a capacidade estatal constitui o conjunto de competências essenciais que as instituições governamentais possuem, ou devem possuir, para a consecução dos objetivos públicos. Entretanto, a natureza multidimensional do construto ‘capacidade estatal’ implica um grande desafio de pesquisa para a academia científica e um grande desafio de gerenciamento para os gestores públicos. Nosso objetivo consistiu na construção de uma medida de desempenho na expectativa de avançar empiricamente nos estudos sobre esse conceito. Marco teórico: a criação do Índice de Capacidade Estatal (SCI) seguiu os mesmos procedimentos do Índice de Desenvolvimento Humano (IDH). Método: a busca de variáveis (proxies) que estejam atinentes ao contexto brasileiro e que permitam, empiricamente, a mensuração e operacionalização da capacidade estatal se deu mediante extensa revisão de literatura. Logo, o SCI permitiu o exame geral do construto, ‘capacidade estatal’. Resultados: os resultados ressaltaram disparidades nas estruturas administrativas municipais de Minas Gerais. Conclusão: sugere-se a necessidade de incentivos e investimentos nas dimensões que abrangeram o Índice de Capacidade Estatal, a saber: administrativa, política e fiscal.

In recent decades, there has been an institutional shift in the literature on authoritarian regimes, with scholars investigating the role of political institutions, such as elections and political parties, in shaping regime stability and economic performance. However, scant attention has been devoted to the effect of political institutions on policy outcomes, and more specifically, on income inequality. This paper adds to this debate and sheds light on the role of formal and informal institutions, on the one hand, and state capacity, on the other, in influencing levels of income inequality in autocracies. We argue that, while the presence of elections and multiparty competition creates more favourable conditions for the adoption of redistributive policies, state capacity increases the likelihood of successfully implemented policy decisions aimed at reducing the level of inequality. Our empirical analysis rests on a time-series cross-sectional dataset, which includes around 100 countries from 1972 to 2014. The findings indicate that both political institutions and a higher level of state capacity lead to lower levels of income inequality in authoritarian contexts.

This study focuses on establishing a novel heuristic algorithm for life-cycle performance evaluation. Special attention is given to decision-making algorithms for concrete-filled steel tubular (CFST) arch bridge maintenance. The main procedure is developed, including the ultimate loading-capacity modeling of CFST members, multi-parameter selection, ultimate thresholds presetting based on the finite element method, data processing, crucial parameters determination among sub-parameters, multi-parameter regression, ultimate state prediction, and system maintenance decision-making suggestions based on the multi-parameter performance evaluation. A degenerated ultimate loading-capacity model of CFST members is adopted in the finite element analysis and multi-parameter performance assessment. The multi-source heterogeneous data processing and temperature-effect elimination are performed for the data processing. The key sub-parameters were determined by the Principal Component Analysis method and the Entropy-weight method. The polynomial mathematical model is used in the multi-parameter regression, and the ±95% confidence bounds were verified. The system maintenance decision-making model combines the relative monitoring state, the relative ultimate state by the numerical analysis, and the relative residual life of degenerated members. The optimal system maintenance decision-making suggestions for the bridge maintenance system can be identified, including the most unfavorable maintenance time and parameter index. A case study on a CFST truss-arch bridge is conducted to the proposed algorithms. The obtained results demonstrated that the crack width deserves special attention in concrete bridge maintenance. Additionally, these technologies have enormous potential for the life-cycle performance assessment of the structural health monitoring system for existing concrete bridge structures.

In this paper we posit that the trajectory of structural-economic transformations in Ecuador between 2008 and 2014 can be understood from the perspective of state theory. Specifically, we argue that strengthening state authority in Ecuador has come at the expense of state capacities: by positioning the state in a place of ‘exceptional authority’, governmental actions sidelined the development of formal and informal networks between state and non-state actors, such as industrialists. Furthermore, we show that state capacities have been further undermined by internal divisions within bureaucratic structures and an eclectic process of leadership formation at the level of the state’s bureaucracy. Combined, these processes have resulted in a hybrid state form: a state with high degrees of authority that coexist with low levels of institutional and organizational capacity – a state form we have termed an ‘Exceptionalist State’.

China’s increased trade with, and investment in, Africa have boosted the continent’s economic growth but have also generated considerable controversy. The aggregate data on China’s overseas direct investment (ODI) in African countries reveal that China’s share of the stock of foreign investment is small, though growing rapidly. China’s attraction to resource-rich countries is no different from Western investment. China’s overall ODI is uncorrelated with a measure of rule of law, whereas Western investment favors the better governance environments. As a result, Chinese investment in strong and weak governance environments is about the same, but its share of foreign investment is higher in the weak governance states. Micro data from MOFCOM’s database on registered Chinese firms investing in Africa between 1998 and 2012 provide a different perspective. Key words in project descriptions are used to code the investments into 25 sectors. This database captures the small and medium private firms investing in Africa. Contrary to common perceptions, there are few projects in natural resource sectors. Most projects are in services, with a significant number in manufacturing as well. Country-sector-level regressions based on firms’ transaction-level data find that Chinese ODI, both horizontal and vertical, is profit-driven, like investment from other countries. In particular, regressions show that Chinese ODI is relatively more concentrated in skill-intensive sectors in skill-abundant countries but in capital-intensive sectors in capital-scarce countries. These patterns are mostly observed in politically unstable countries, suggesting stronger incentives to seek profits in tougher environments.

Complexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data points of training dataset for developing data-driven techniques, Incremental Dynamic Analyses (IDAs) were performed considering 165 RC MRFs with two-, to twelve-Story elevations having the bay lengths of 5.0 m, 6.1 m, and 7.6 m assuming near-fault seismic excitations. Then, important structural features were considered in datasets to train and test the ML-based prediction models, which were improved with innovative techniques. The results show that improved algorithms have higher R 2 values for estimating the Maximum Interstory Drift Ratio (IDR max ), and two improved algorithms of artificial neural networks and extreme gradient boosting can estimate the Median of IDA curves (M-IDAs) of RC MRFs, which can be used to estimate the seismic limit-state capacity and performance assessment of existing or newly constructed RC buildings. To validate the generality and accuracy of the proposed ML-based prediction model, a five-Story RC building with different input features was used, and the results are promising. Therefore, graphical user interface is introduced as user-friendly tool to help researchers in estimating the seismic limit-state capacity of RC buildings, while reducing the computational cost and analytical efforts.

Weak state capacity is one of the most important explanations of civil conflict. Yet, current conceptualizations of state capacity typically focus only on the state while ignoring the relational nature of armed conflict. We argue that opportunities for conflict arise where relational state capacity is low, that is, where the state has less control over its subjects than its potential challengers. This occurs in ethnic groups that are poorly accessible from the state capital, but are internally highly interconnected. To test this argument, we digitize detailed African road maps and convert them into a road atlas akin to Google Maps. We measure the accessibility and internal connectedness of groups via travel times obtained from this atlas and simulate road networks for an instrumental variable design. Our findings suggest that low relational state capacity increases the risk of armed conflict in Africa.

Of the 17 Sustainable Development Goals articulated by the United Nations, number one is the elimination of extreme poverty by 2030. While future economic growth should continue to reduce poverty, it will not solve the problem by itself; thus, there is a potentially important role for national-level transfer programs that assist poor families in developing countries. Such programs are often run by developing country governments. Many countries have implemented transfer programs that seek to target beneficiaries: that is, to identify who is poor and then to restrict transfers to those individuals. Some people have begun to advocate for “universal basic income” programs, which dispense with trying to identify the poor and instead provide transfers to everyone. We begin by considering the universal basic income as part of the solution to an optimal income-taxation problem, focusing on the case of developing countries, where there is limited income data and inclusion in the formal tax system is low. We examine how the targeting of transfer programs is conducted in these settings, and provide empirical evidence on the tradeoffs involved between universal basic income and targeted transfer schemes using data from Indonesia and Peru—two countries that run nationwide transfer programs that are targeted to the poor. We conclude by linking our findings back to the broader policy debate on what tools should be preferred for redistribution, as well as the practical challenges of administering them in developing countries.

Why do infrastructure projects that are similar in nature develop along starkly different trajectories? This question sheds light on the varying state capacity of developing countries. Divergent from structural explanations that stress external agency and institutional explanations that emphasize bureaucratic capacity, I propose a political championship theory to explain the variance in states capacity of infrastructure delivery. I argue that when a project is highly salient to leaders’ survival, leaders commit to the project; leaders with strong authority build an implementation coalition, leading to higher effectiveness. I trace the process of the Standard Gauge Railway in Kenya and Addis-Djibouti Railway in Ethiopia, relying on over 180 interviews. This research highlights the individual agency within structural and institutional constraints, a previously understudied area in state capacity.

Effective states govern by some combination of enforcement and voluntary compliance. To contain the COVID-19 pandemic, a critical decision is the extent to which policy makers rely on voluntary as opposed to enforced compliance, and nations vary along this dimension. While enforcement may secure higher compliance, there is experimental and other evidence that it may also crowd out voluntary motivation. How does enforcement affect citizens’ support for anti–COVID-19 policies? A survey conducted with 4,799 respondents toward the end of the first lockdown in Germany suggests that a substantial share of the population will support measures more under voluntary than under enforced implementation. Negative responses to enforcement—termed control aversion—vary across the nature of the policy intervention (e.g., they are rare for masks and frequent for vaccination and a cell-phone tracing app). Control aversion is less common among those with greater trust in the government and the information it provides, and among those who were brought up under the coercive regime of East Germany. Taking account of the likely effectiveness of enforcement and the extent to which near-universal compliance is crucial, the differing degrees of opposition to enforcement across policies suggest that for some anti–COVID-19 policies an enforced mandate would be unwise, while for others it would be essential. Similar reasoning may also be relevant for policies to address future pandemics and other societal challenges like climate change.