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Two major earthquakes which struck Northwestern Turkey in 1999 exposed rampant corruption involving construction and zoning code violations. The government’s relief efforts were tainted by corruption as well, and exhibited a great deal of incompetence. How voters responded to these in the next election held in 2002 is investigated. The fact that different group of parties were responsible for the construction of the shoddy buildings, and for the corruption and mismanagement related to relief, provided us with a unique opportunity to determine whether and how the electorate punished the culprits for each of these. The purpose of this paper is to shed light also on the new party system which emerged in Turkey after 2002.

Vote equations are estimated for the seven major political parties. These are fitted to cross-provincial data individually, using ordinary least squares and robust regression methods, and as a system, using seemingly unrelated regressions procedures. The same picture emerges from each of these methods.

Not just those ruling at the time of the earthquakes, but also other parties which were in power when the substandard buildings, were built were held accountable by the electorate. Furthermore, the Turkish voters appear to have allocated the blame rationally, taking into consideration the division of labor in the central government, and the relative influences the parties had on local administrations. Reaction of the voters to government incompetence and corruption was one of the factors which resulted in the emergence of a new party system. In 2002, the AKP, established only a year before, captured almost all of the far-right Islamist, about half of the far-right nationalist, and more than half of the center-right votes in 2002.

Corruption usually makes little difference in the fortunes of politicians. Some recent studies suggest that it takes more than just exposure of corruption to get the voters to react. Politicians pay a significant price only when the corruption touches all political parties across the board, is not accompanied by good governance, and competent non-corrupt alternatives are available. The results provide support for this assertion from the natural experiment that has taken place in Turkey.

This research investigates the complex relationship between economic policy uncertainty (EPU), energy consumption and institutional factors in the Gulf region. The purpose of this study is to examine how institutional factors moderate the impact of EPU on energy consumption in Gulf countries.

This paper uses the dynamic panel autoregressive distributed lag (PARDL) method, over a period stretching from 1996 to 2021 in the Gulf countries.

The results show that, only in the long term, EPU has a positive and significant impact on energy consumption, suggesting that increased EPU leads to increased energy use. Furthermore, this study found that, only in the long term, government effectiveness and regulatory quality have positive and significant effect on energy consumption. Accordingly, the two institutional factors play a moderating role in the EPU−energy consumption nexus.

This study highlights the importance of considering the time dimension when formulating energy and economic policies in Gulf countries. Policymakers should take into consideration the nature of these relationships to make informed decisions that promote energy efficiency and economic stability in the region.

To the best of the authors’ knowledge, this is the first study examining the relationship between EPU and energy consumption in the Gulf countries while incorporating the role of institutional factors as potential mediators.

The purpose of this paper is to focus on global energy consumption using the economic growth nexus, the prevalent energy hypothesis at a global level and the impact of the main historical events assessed for the period from 1965 to 2015.

Given the confirmed presence of endogeneity and cointegration between energy consumption and economic growth, a vector error correction with structural dummies model was used. Furthermore, the impulse-response functions and variance decomposition were computed to evaluate the variables’ dynamics.

Bi-directional causality running from energy consumption to economic growth was found, both in the short and long-run, supporting the feedback hypothesis. It is proved that the 2008 crisis impacted on the global energy–growth nexus. Furthermore, there is evidence of the impact of the 1990s oil price shock on the nexus. Innovations in energy consumption have a positive impact on economic growth; however, this impact tends to be null in the long run.

The results suggest that at a global level, any energy policy should be carefully designed in order not to hamper economic growth. Countries should not remain indifferent to the policies that other countries might follow. Very few historical crises impacted on the global energy–growth nexus.

This paper offers a different approach to the study of the energy–growth nexus. The energy–growth nexus is analysed in the major macroeconomic aggregate. Global variables reveal their relevance as a benchmark in the energy–growth nexus. Furthermore, this paper arrives at some conclusions about how historical crises impact on global relationships.

The main purpose of this study is to detect homogeneous housing market areas among 196 districts of 5 major cities of Turkey in terms of house sale price indices. The second purpose is to forecast these 196 house sale price indices.

In this paper, the authors use the monthly house sale price indices of 196 districts of 5 major cities of Turkey. The authors propose an autoregressive (AR) model-based fuzzy clustering approach to detect homogeneous housing market areas and to forecast house price indices.

The AR model-based fuzzy clustering approach detects three numbers of homogenous property market areas among 196 districts of 5 major cities of Turkey where house sale price moves together (or with similar house sales dynamic). This approach also provides better forecasting results compared to standard AR models by higher data efficiency and lower model validation and maintenance effort.

In this study, the authors could not use any district-based socioeconomic and consumption behavioral indicators and any discrete geographical and property characteristics because of the data limitation.

The finding of this study would help property investors for establishing more effective property management strategies by taking different geographical location conditions into account.

From the government side, knowing future rises, falls and turning points of property prices in different locations can allow the government to monitor the property price changes and control the speculation activities that cause a dramatic change in the market.

There is no previous research paper focusing on neighborhood-based clusters and forecasting house sale price indices in Turkey. At this point, it is the first academic study.