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The study is called for to eliminate the noise between the significant macro variables from the perspective of the cause-and-effect approach to indicate why and how the return of solar projects is being affected by these.

The study aims to investigate the spread between unit selling electricity prices of a monthly production of 250 KW solar project installed in Türkiye and USD/TRY.

A relational framework is designed by drawing on the variables determined as crude oil prices, United States (US) 2-year yield, Dollar Index (DXY), USD/TRY, the annual inflation rate of Türkiye, and unit selling electricity prices. Then, a multivariate approach is performed through Matlab to analyse the correlational relationships and structure the curve estimation models.

The observations show that the gradually rising spread between unit selling electricity price and USD/TRY signals the reduction in return-on-investment rate of solar energy projects because of the particular causes of the European energy crisis by the reason of Russia and Ukraine war and escalating risks in DXY and US treasury yields as a result of federal fund rate hikes against inflationary pressures. Solar energy investments are delicate instruments to global oil shocks and higher DXY in controlling Inflation and currency volatility; therefore, resilient policies should solicit the demand because of environmental and economic reasons to reduce the external dependency of Türkiye.

In this chapter, the authors consider the role of time for research in occupational stress and well-being. First, temporal issues in studying occupational health longitudinally, focusing in particular on the role of time lags and their implications for observed results (e.g., effect detectability), analyses (e.g., handling unequal durations between measurement occasions), and interpretation (e.g., result generalizability, theoretical revision) were discussed. Then, time-based assumptions when modeling lagged effects in occupational health research, providing a focused review of how research has handled (or ignored) these assumptions in the past, and the relative benefits and drawbacks of these approaches were discussed. Finally, recommendations for readers, an accessible tutorial (including example data and code), and discussion of a new structural equation modeling technique, continuous time structural equation modeling, that can “handle” time in longitudinal studies of occupational health were provided.

Conceptual paper purpose – The purpose of this chapter is to examine a new conceptual model of addiction and interpret the results from delay discounting studies in light of this new perspective.

Methodology/approach – To accomplish this we (1) introduce this new conceptual model, (2) briefly review executive function, including evidence for executive dysfunction among the addicted, (3) describe the unique relationship of temporal discounting to the new model and executive dysfunction, and (4) reinterpret the discounting literature in light of this new conceptual model.

Findings – Addicted individuals discount the future more than controls. This is consistent with greater relative activation of the impulsive system and decreased relative activation of the executive system. It also supports the new conceptual model of addiction.

Research implications – The new model provides a model for understanding the observations from the broader area of research in temporal discounting.

Originality/value of chapter – Given the view of executive function as important for the cross-temporal organization of behavior, we think that temporal discounting, the valuing of future commodities, qualifies this process to be included as an executive function.

The Epidemiologic Transition can help us understand a fundamental puzzle about aging. The puzzle stems from two seemingly contradictory facts. The first fact is that death rates from noninfectious degenerative maladies – the so-called diseases of aging – increase as people age. It seems to be at odds with the historical fact that for nearly a century in which people were aging more than ever before, the aggregate rates of such diseases have been decreasing. In what sense can both be true? Crucial to resolving the puzzle are the age-profiles of such diseases in cohorts that grew up in the different regimes of the Transition. For each cohort, noninfectious diseases had increased with age, resulting in an upward-sloping age profile, which affirms the first fact. As the regimes were transitioning from the Malthusian to the modern one, however, the profiles of successive cohorts had been shifting downward: death rates from noninfectious diseases were shrinking at each age, signifying the newer cohorts’ greater aging potentials. The shifting profiles had been renewing the cohort mix of the population, shaping the century-long descent of such diseases in aggregate, giving rise to the historical fact. The profiles had shifted early in the cohorts’ adult years, associating closely with the newer epidemiologic conditions in childhood. Those conditions appear to be a circumstance under which aging potentials of cohorts could be misgauged, including in one troubling episode in the first half of the nineteenth century when the potentials had reversed.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.