Purpose: One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.Design/methodology/approach: In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.Findings: The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.Originality/value: This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.

Banks entering a developing market face a lot of uncertainty about the risks involved in lending. This paper models the effective factors on default rate (DR) loans to small and medium size enterprises (SMEs) in Iran based on the case study of branches of Melli Bank in Khorasan Razavi province. For this purpose a set of data about loans made to 300 SMEs between years 2004 to 2015 and Delphi, SEM and Tobit models were applied. Results of Delphi technique indicated that 48 factors affect the DR. The structural equation model (SEM) estimations showed that between 10 latent variables which describe the DR, the “loans properties” latent variable have the most effect. Also, findings of Tobit econometric model stated that between 48 variables which affect the DR, “loan volume” variable has the most effect. These and other factors emphasize the need for SMEs credit scoring in developing countries.

یکی از عوامل مهم تأثیرگذار در رابطه نابرابری و رشد اقتصادی، سرمایه ‌انسانی است. بسته به مقدار انباشت سرمایه انسانی در یک کشور، چگونگی تأثیرگذاری نابرابری بر رشد اقتصادی متفاوت خواهد بود. بی‌توجهی به این مقوله در مطالعات نظری و تجربی باعث ایجاد خطای تصریح الگو و دستیابی به نتایج پراکنده و متناقضی خواهد شد که در مطالعات داخلی نیز به آن توجه نشده است. در این مطالعه تأثیرگذاری نابرابری بر رشد در ایران و در سطوح مختلف سرمایه انسانی، با استفاده از داده‌های سری زمانی مربوط به سال‌های 1348 تا 1393 بررسی شده است. الگوسازی داده‌ها بر اساس روش رگرسیون آستانه‌ای است که نسبت به سایر روش‌های تخمین، برآوردهای سازگارتری ارائه می‌کند. نتایج حاصل از برآورد الگو نشان می‌دهد در ایران، تأثیرگذاری نابرابری درآمد بر رشد اقتصادی همواره منفی بوده است، اما تأثیر منفی نابرابری بر رشد اقتصادی همگام با بلوغ اقتصاد و افزایش سطح سرمایه انسانی کاهش می‌یابد، همچنین تأثیرگذاری توأمان سرمایه فیزیکی و سرمایه انسانی بر رشد اقتصادی، همگام با افزایش سطح سرمایه انسانی در مراحل بلوغ اقتصاد افزایش می‌یابد. طبقه‌بندی : I24, I25,O47, P46, D31