Oil income shocks and economic growth in Iran

The aim of this paper is to study the relationship between oil revenue shocks and output growth in Iran by Adopting an SVAR model over the period 1959–2008. The results indicate that positive and negative oil revenue shocks significantly affect output growth positively and negatively respectively and these effects are asymmetric. While negative oil revenue shocks adversely affect the economic growth, the resource curse impedes the expected positive effects of positive oil shocks. In order to overcome the harmful effects of oil booms and busts, the establishment of oil stabilization and saving funds, diversifying economy, delinking government expenditure from oil revenues and introducing fiscal rules into the budget seems crucial for Iran economy.     

The temporal variation of cost-efficiency in Switzerland’s hospitals: an application of mixed models

This paper uses a mixed effects model to examine the temporal variation of cost efficiency in Switzerland’s general hospitals. The variations in total costs, the number of empty beds and the length of hospital stays are analyzed using financial data from a sample of 168 hospitals operating from 1998 to 2003, as well as hospitalization records disaggregated to Diagnosis Related Groups. Individual intercepts and random coefficients are used to account for the unobserved time-invariant heterogeneity and the differences in temporal patterns across hospitals and DRG categories. The analysis illustrates the usefulness of mixed models to account for unobserved factors such as quality, with a relatively weak assumption that their temporal variations, rather than their initial levels, be uncorrelated with efficiency changes. The results indicate that hospitals have adopted measures to curtail hospitalizations and reduce empty beds. The extent and effectiveness of these measures vary significantly across individual hospitals. However, there is no evidence in favor of a particular ownership type or subsidization regime. While the link between reduction rates of empty beds and gains in cost-efficiency is statistically significant, the expected association between shortening hospital stays and cost-efficiency cannot be clearly established in the data.

Ex-post favoring ranks: a fairness notion for the random assignment problem

We introduce two notions of ex-post fairness, namely ex-post favoring ranks (EFR) and robust ex-post favoring ranks, which consider whether objects are received by those agents who have the highest rank for them. We examine their compatibility with standard properties of random assignments and state some impossibility theorems. We also propose and formalize a revised version of the Boston mechanism and prove that it provides an EFR random assignment.

     

Developing a multiple-criteria decision analysis for green economy transition: a Canadian case study

ABSTRACT

Identifying planning strategies for the transition to a green economy is a formidable challenge. We proposed a novel multiple-criteria decision analysis model which can quantitatively identify the socio-economic and environmental impacts of various government and public policies. We applied the model to four practical scenarios in Canada for determining the optimal final demand that maximizes the country's GDP and employment while minimizing GHG emissions for small, short-term changes. As a result, the model suggested potential ways to simultaneously achieve a GDP growth of 2.5 billion CAD and creation of over 25,000 new jobs, and a saving of 2514 kt CO₂. As per the final demand, the electrification of domestic heating and transport should be more promoted. The proposed analysis tool will provide decision-makers with the ability to explore the design and effects of policy reforms, regulatory changes, and targeted public expenditure strategies, thereby overcoming barriers towards a green economy.     

Probability forecast of downturn in U.S. economy using classical statistical decision theory

This paper presents a methodology for producing a probability forecast of a turning point in U.S. economy using Composite Leading Indicators. This methodology is based on classical statistical decision theory and uses information-theoretic measurement to produce a probability. The methodology is flexible using as many historical data points as desired. This methodology is applied to producing probability forecasts of a downturn in U.S. economy in the 1970–1990 period. Four probability forecasts are produced using different amounts of information. The performance of these forecasts is evaluated using the actual downturn points and the scores measuring accuracy, calibration, and resolution. An indirect comparison of these forecasts with Diebold and Rudebusch's sequential probability recursion is also presented. It is shown that the performances of our best two models are statistically different from the performance of the three-consecutive-month decline model and are the same as the one for the best probit model. The probit model, however, is more conservative in its predictions than our two models.     

Modified CADF and CIPS Panel Unit Root Statistics with Standard Chi‐squared and Normal Limiting Distributions

In an influential paper Pesaran (‘A simple panel unit root test in presence of cross‐section dependence’, Journal of Applied Econometrics, Vol. 22, pp. 265–312, 2007) proposes two unit root tests for panels with a common factor structure. These are the CADF and CIPS test statistics, which are amongst the most popular test statistics in the literature. One feature of these statistics is that their limiting distributions are highly non‐standard, making for relatively complicated implementation. In this paper, we take this feature as our starting point to develop modified CADF and CIPS test statistics that support standard chi‐squared and normal inference.     

Fingolimod versus natalizumab in patients with relapsing remitting multiple sclerosis: a cost-effectiveness and cost-utility study in Iran

Aims: Multiple sclerosis (MS) is a chronic, autoimmune, and inflammatory disease. If the first-line medicines are not effective enough, specialists will prescribe second-line medicines, such as natalizumab and fingolimod. This study aimed to compare the cost-effectiveness and cost-utility of fingolimod with those of natalizumab in patients with relapsing-remitting multiple sclerosis (RRMS) in Iran, Fars province in 2016.

Materials and methods: This study was a cost-effectiveness and cost-utility study in which a Markov model was used. The study used the census method to evaluate 81 patients with MS in Iran, Fars province who were being treated with fingolimod and natalizumab. In this study, costs were collected from the societal perspective, and the outcomes were the mean of relapse avoided rate and QALY. The cost data collection form, Kurtzke Expanded Disability Status Scale, and EQ-5D-3L questionnaire were used to collect the required data.

Results: The results showed that, compared to natalizumab, patients who used fingolimod had decreased costs (58,087 vs 201,707), increased QALYs (8.09 vs 7.37), and a better relapse avoided rate (6.27 vs 5.83) per patient over the lifetime. The results of the sensitivity analysis showed that the results of the study were robust. Also, the results of the scatter plots showed that fingolimod was more cost-effective based on the QALY and relapse avoided rate in 62% and 56%, respectively, of the simulations for the thresholds below $15,657 for the studied patients.

Conclusions: According to the results of this study, the cost-effectiveness and cost-utility of fingolimod were higher than those of natalizumab. Therefore, it is recommended that treatment with fingolimod be the first priority of second-line treatment for MS patients, and policy-makers and health managers are encouraged to make efforts in order to increase insurance coverage and reduce the out-of-pocket payments of these patients.     

Inflation and the Income Share of the Rich: Evidence for 14 OECD Countries

This paper examines the distributional implications of inflation on top income shares in 14 advanced economies using data over the period 1920–2016. We use local projections to analyze how top income shares respond to an inflation shock, and panel regressions in which all variables are defined as 5-year averages to examine the impact of inflation on the position of the top-one-percent in the long run. Our findings suggest that inflation reduces the share of national income held by the top 1 percent. Furthermore, we find that inflation shocks and long-run inflation have similar effects on top income shares.     

Do large recessions reduce output permanently?

We apply a recent quantile autoregression unit root test to US GDP. The test takes into account that the transmission of a shock might depend on the sign and the size of the shock. We find that positive and negative shocks including large recessionary shocks like the 2008/2009 crisis have permanent effects on output.