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What do you think are the biggest negative social and economic impacts of double-digit and currently rising inflation?
Central banks are raising interest rates in an attempt to contain rising inflation, to curb the rise in inflation and, in the next quarters or perhaps years, to bring inflation down to a low single-digit level, to the inflation target of monetary policy. However, commercial banks are raising interest rates on deposits and bank deposits to a limited extent. Interest rates on new government bond issues are also rising slowly. By contrast, interest rates on bank loans offered by commercial banks are rising much faster. The rising cost of money causes a decline in lending of mortgages, business loans, consumer loans, etc. The rate of economic growth is falling. Enterprises ai companies are holding back on new investments. Repayment instalments on long-term loans that have been granted at a variable interest rate are rising. Financial risks are increasing, including credit risks, liquidity risks, debt risks, and the profitability of production processes is falling. The risk of a significant rise in unemployment and the emergence of stagflation in 2023 is emerging. The scale of social unrest in many countries around the world is increasing. In addition, the economic downturn is being exacerbated by rising energy and fossil fuel prices, i.e. the currently developing energy crisis.
In view of the above, I address the following question to the esteemed community of researchers and scientists:
In your opinion, what are the greatest negative social and economic impacts of double-digit and currently rising inflation?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Regards,
Dariusz Prokopowicz
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Inflation appears even before the increase in energy prices and even before the war on the territory of Ukraine. In order to counteract the effects of the debt crisis from 2010 and after that the effects of the pandemic crisis with COVID-19, ECB monetary policies were so abundant in providing money in the Eurozone. Now when inflation is high the ECB is increasing the interest rate by a small % (0.75). I think that ECB now is very cautious about the possible effects of this interest rate increase on the EU economies.
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An economic evaluation of the natural capital is essential to understand its loss for human developmental activities.
Moreover, valuation methods have always underestimated the economic costs associated with natural resources. Nevertheless, they at least provide a vision for policymakers to decide development against conservation.
How could valuations methods be improved, and integrated into holistic policy and decision making?
I would request my colleagues to enlighten, regarding its importance from your years of research experience.
Regards
Gowhar Meraj
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Thank you very much for highlighting this issue. I have now deleted the link to the paper. I have also added some questions and hope that you will provide some valuable insights.
Sincerely yours
Gowhar Meraj
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Whenever I search for papers on google scholar regarding my topic i.e. 'Economic Evaluation of the Impact of Air Pollution on Public Health in Delhi', most research papers are based on Atmospheric Sciences. I intend to focus my review on the aspect of Economics. Kindly help me with the most relevant search engines or techniques, that might make my search for relevant articles easy.
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If you have one or more papers related to your topic, I suggest you mine the bibliographies for leads. You will begin to find the researchers writing on the topic and who is in their network. Continue this process until you no longer find new names.
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Please help. I am looking for Economic Evaluation Reference of any of the following plants:
Wedelia chinensis
Talinum portulacastrum
Tribulus terrestris
Leucas aspera
Rauvolfia serpentine
Ocimum canum
Bacopa monnieri
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Hello,
I am new to fmm. If I run a two component mixture model I will have two sets of predicted values (one for each component). I can also generate the posterior prob and the most likely latent class membership. How do I combine these two sets of values to produce single predicted values which correspond  to my dependent variable?
Thanks
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Autism is a disorder which effects the behavioral skills of a child for the rest of his/ her life. Trying to estimate the cost of different variables to asses the cost benefit effectiveness of a Communication centered Parent mediated intervention for Autism in South Asia. Maximum literature is from the developed parts of the world which makes it in appropriate to adopt similar tools in Low and Middle Income Countries in South Asia.
For further details kindly refer to this link for the project description.
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Thank you for the text. It was very helpful in understanding the broader context of costs involved and research practices.
I am presently developing a cost of Illness Inventory which will collect information on the monetary and time costs related with the child from the parents. I am having difficulties in capturing opportunity cost of the parent who are willing to do a job but cannot do so.
Given scarcity of data and literature on autism in India it difficult to assume such costs. It seems very speculative.
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As shown by our experience in evaluating small projects (up to 1-2 million) - the implementer (both the CSO and the International Organizations) have neither the resources nor the capacity to make a high quality project evaluation. The result is a game of imitation evaluation:
The customer puts in ToR 20-30 evaluation questions (which he found in online) with no budget, with limit of 15-20 working day (including field mission), ask detailed methodology without access to project documentation etc.
The evaluator taking his standard offer, change keywords and use other tips to imitate tailor-made methodology. Later, as such calls usually for individuals, the evaluator is limit his/her work by interview and desk review without in-depth stakeholders analysis, triangulation etc.
Usually such project has no clear logical model, no any M&E system. So actually there is no any chance to talk seriously about efficiency and effectiveness at all.
But 80% of calls for proposals in developing countries are such.
Anyone familiar with any mechanism for organizing a high-quality evaluation of a small-scale project without profaning the process itself? Are there any publication or tools/standardized methodology solving such case? If not - Is there a demand for such a tool / methodology? Do you know professors who may be interested in such research and development?
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Haji Saediman thank you very much for your opinion!
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I need to run an economic evaluation model of 6 drugs based on secondary data of a network meta-analysis study which has covered 21 drugs. This study also has reported separate pairwise head to head data. My concrete question it is that due to the use of only parts of the whole analyses (6 drugs out of 21) which of the following approaches is accurate?
1. Extracting required data (6 drugs out of 21) through pairwise analysis or
2. Extracting required data (6 drugs out of 21) through network meta-analysis
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Pairwise analysis may be more appropriate because it includes direct comparison only while network meta-analysis is the combination of direct and indirect comparisons.
Also, you can use both approaches in your analysis, and report both results in the manuscript.
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I want to forecast volatility with GARCH, EGARCH and GJR-GARCH. How do I obtain the RMSE, MAE and MAPE. The problem now is that I am using a mean equation and the values reported in the little table on side are for stock returns. I need the same thing for volatility. Any idea except from calculating them by hand?
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The command accuracy() under forecast package in R returns a range of forecast accuracy measures including:
  • ME: Mean Error
  • RMSE: Root Mean Squared Error
  • MAE: Mean Absolute Error
  • MPE: Mean Percentage Error
  • MAPE: Mean Absolute Percentage Error
  • MASE: Mean Absolute Scaled Error
  • ACF1: Autocorrelation of errors at lag 1.
You can generate the necessary forecasts in EViews and use forecast and actual values to calculate loss measures in R.
accuracy(f, x, test = NULL, d = NULL, D = NULL, ...)
where argument f - forecasts and x- is realized values.
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Dear Economists I have some theoretical insights into time series analysis but having difficulty in using it on computer based programs like E views I need some tutorial help and if some one guide me to a step wise descriptive layouts of E Views for using different models it would be a great help for me
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Dear all:
Please find attached two books that provide accurate step-by-step guide to financial econometrics using Eviews.
Regards,
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Dear Experts,
I am looking forward to apply Statistical Package as part of my Health Technology assessment in terms of Economic analysis. I have been using SPSS from my previous projects but there are certain limits e.g.: I can not carry out Markov Chain model in SPSS properly. Thus I am looking forward to step into R Programming. Is there any recommendation you can provide then it would be helpful since It is time consuming  and I am looking forward to powerful tool in which I can perform necessary tasks for Health Economics Evaluation.
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For a start, R is free, and with RStudio to run it it's getting very useable. 
R is also far more powerful than SPSS. SPSS has no great presence in economics for good reasons. 
I'd recommend you take the DataCamp basic R course (take notes as you go!) and get to grips with R
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I have tried to use BenMAP-CE but it does not allow thresholds for ozone to be inputted into the system and the guide to use it is outdated. The newer version is different than described and it will not allow me to continue due to error and incorrect inputs. The manual is wrong after the newer version 1.08 was released.
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Please refer to the article
"A Health Impact Assessment of Proposed Public Transportation Service Cuts and Fare Increases in Boston, Massachusetts (U.S.A.)" by
Peter James,  Kate Ito , Jonathan J. Buonocore , Jonathan I. Levy  and Mariana C. Arcaya
at
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The research which will be mainly based on first-hand data. 
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An opinion from a different field - health technology assessment.
In real life conditions you often have to mix ex-ante and ex-post data. First step should be to design your model - the representation of the reality which is relevant for your question. The type of model - decision tree, Markov, discrete events, differential equations, agent based or other more dynamic types - then shows you, which parameters you need. Values for parameters can come from measurement, literature or sometimes expert opinion. The point is, that you take the best available values and discuss their limitations in form of an extensive sensitivity analysis of your model results. You may even compare model results derived from different assumptions for specific parameters.
So if ex-ante and ex-post data is available - compare them.
If ex-post is available and ex-ante has to be collected (at some cost) perform a value of information analysis to look if the additional effort brings more reliable results - as part of the sensitivity analysis.  
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I have choice experiment data for estimating farmer's WTP for irrigation water. I asked farmers to choose from a set of 5 choice sets, each choice set containing 3 alternatives and a current status scenario. From each choice set they chose only 1 alternative. I am planning to use clogit to analyze my data. My dependent variable is a binary choice of whether they chose the alternative or not. If i do this each farmer will have 20 mutually exclusive observations from which 5 are selected as yes and the rest as no. Is this approach correct? or there is a better way of defining my dependent choice variable?
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Ask Wanggi Jaung at UBC - he would have good ideas.
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I have a survey question that asks: Is Ontario on the right track or headed in the wrong direction these days?".  
Technically speaking, what does this measure in terms of the political science literature? Mood? Affective evaluation of the economy? Is this a form of sociotropic economic evaluation?
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Hi Simon,
I think it would be necessary to explain what is meant by positive and negative track since one's definition of positive maybe another person's negative and vice versa. From an economics perspective, you would want to come up with a positive statement such that the respondent is not left to define the parameters with which he/she will answer your question. If you will go by the neo-classical school, you may want to ask whether the international trade policy of lowering further barriers to trade is overall positive for the national economy or not. 
Best regards,
Pricivel 
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Dear Professors
I have estimated the export supply function for aggregate, primary and manufactured exports. i have derived the long run and short term elasticity Unrestricted ARDL and Restricted ECM models respectively. but my question is that what is logic behind huge difference in long run and short term effect of production capacity and capacity utilization on export growth. i paste the results please guide me what is problem. Either it is correct or wrong
                                           long Run                          short run
             production capacity capacity utilization prod- capacity  cap- utilization
aggregate       3.002             -2.199                      886.014          -1.172
                          (4.706)           (-4.176)                    (0.315)            (-1.663)
primary               1.885         -2.160                     - 7077.677        -0.468
                          (6.526)       (-3.079)                     (1.272)            (-0.394)
manufactured      3.507        -1.219                          2328.317    -0.833
                           (5.371)      (-1.743)                       (0.657)       (-1.027)
in () is t-statistic value
My question is that why the coefficient size especially of  production capacity is so high in short run because i have taken all variable in log form second why it is negative in in the case  primary exports and why it is highly insignificant in short run 
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Dear Irshad,
If you measure capcity utlisation as deviations from trend of real GDP, then for usual trend calculations, the deviations (absolute or percentage?) show differnt signs. Therefore a log-transformation is not possible. I assume that you use ln(GDP/trend GDP) in your estimation.  As capacity mearure, you seem to use real trend GDP. Because of the strong correlation between the variables, the coefficients are likely to be highly biased.  In fact, you seem to use the following equation (not complete):
dlnX =a*dln(TrendGDP)+b*dln(GDP/Trend)+c*ln(TrendGDP)+d*ln(GDP/Trend)+... or a similar specification. lnTrend is, of course near a linear time trend (for an exponential trend it is exactly linear), and llnTrend is (nearly) a constant.
If X has a strong trend, one can expect too high estimates for a and c and too low  ones for b and d (if not integrated into the third term). High random fluctuations of X are likely to go into a and b (partly compensating each other). Your short-run elasticities are far from any acceptable range, but I would also not accept hte high long-run ones.
From an economic (theoretical) point of view, I do not understand why capacity utilisation should have a strong (positive or negative) influenceon exports. I see much stronger causality in the other direction, higher exports lead to a higher CU.
I propose to abstain from ARDL and ECM and apply simple OLS. A good specification is much, much more important than a highly refined method (often simply used because it is modern).
Best regards,
Anton
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Most of the literature I've come across with respect to planned obsolescence is analyzed mainly from the producer's perspective. I've not come across current  literature on why the consumer would rationally choose lower quality products as opposed to stronger durable goods (except for innovative product theory where the user accepts lower quality product for a distinctive feature, but how does this play in the long run in traditional markets were features are fads and durability remains a factor such as hardware in construction). While I can understand such  behavior on markets such as mobile technology, I find it hard that the incentives are lower in more traditional markets. While it may be argued that this is the product of more marketing efforts, how is this explained with rational agents within modern economic theory?
Any help or feedback is appreciated
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Arturo, both you and Yuri added some interesting points. You specifically asked about the perspective of the consumer.  A few things came to my mind that may help you and they might be best understood with examples.
Light bulbs are commonly used to illustrate planned obsolescence.  Occasionally, this may create a seemingly significant reduction in value to the consumer, and in many cases it does!  However, in the lighting industry I have read that replacing certain specific types of light bulbs before they burn out may save the consumer quite a bit in overall expense. This is especially true with certain light bulbs because at or near the end of their life they can damage other elements (e.g., ballasts and other electronic components) as they have their final burst.  Moreover, the risk of the glass shattering is a concern.  As I recall, the information above came from lighting engineers.  In a related example, this possibly might be the reason some of our classroom projectors have a chip that effectively shuts off the bulb after a set number of hours.  It is also possible that these are attempts to leverage consumers into paying more for less.
A personal example goes in another direction. As a consumer, I enjoy buying some things that are not the most current because of firm's planned obsolescence. For example, I built around a dozen computers for family and friends and the price of the CPU drooped dramatically when a newer & faster processor came out. These would have been state of the art machines a few months earlier; however, now we could have them for a tiny fraction of the cost.
I almost hesitate to mention the next example.  I bought a vehicle for about one percent of its original price that performs almost identically as when it was new. Although it may not last as long as a brand new one, I enjoy almost all of the benefits with a tiny fraction of the cost.  There is more risk and a variety of other factors are involved; however, for some like me, such opportunities are worth it.
In spite of my attempts to add some direct examples that might address your specific question, I certainly am not trying to argue that planned obsolescence is socially desirable as a general proposition.  It is wasteful and frustrating to be forced to discard products that have plenty of useful life remaining just because a firm forces us to abandon it by removing even inexpensive support (e.g., cell phone software updates) or withholding replacement parts for things like cordless tools. 
I hope this helps,
Rob 
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One has to compare the delicate economic reasoning which led Keynes to assume that interest did not affect MPC, or the complex considerations on which Hicks constructs Capital and Time, with the modern axiomatic method that reasons downwards. The former seems to retain a grasp of economic reality even after mathematical cloaking, while the latter seems arid.
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It IS arid.  To "assume an axiom" and then apply reason to develop a theory from which you then proscribe policy, as so many mathematical economists of the post '70's generation appear to do, is no different to the approach taken by the scientists of the Spanish Inquisition and those impositions of belief upon others which are no more than a belief in the rightness of one's own beliefs.
It is not only arid, it is also totally illegitimate in an academic context.  Such an approach to be presented, and even worse when it is accepted, is a demonstration of the extent to which the mainstream of academia has been infiltrated and subverted by commercial, political and other selfish interests seeking fraudulent 'endorsements' and 'validations' from supposedly authoritative sources for their own exploitative schemes.
It should be a criminal offence.....
Rob
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I am trying to find out potential market size for 2 products I am developing and constructing several business model scenarios. I do not know if I should use disease prevalence, health care expenditures, number of cases performed, trends bot away from the private practice model as well as moving procedures away from the hospital setting.
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Hello,
Have you read the Transparency Market Research Report, "Digital Radiology Market - Global Industry Size, Market Share, Trends, Analysis and Forecast, 2012 - 2018"? It indicates that the global radiology systems market is estimated at $9.7 billion in 2012 and expected to reach $13.3 billion by 2018, at a compound annual growth rate of 5.4 percent from 2012 to 2018.
Kind regards,
Monica
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We have followed some 1,500 sophomore girls for about 15 years. They had the opportunity of applying for summer jobs at a Town council, and the applications were thereafter randomly approved by the council. Generally, the effect of a early work experience was significant. However, the sub-group of girls with low grades seemed to benefit enormously. Those that did not get an offer had an average, annual income of about SEK 100,000 (about $14,000) at the age of 30 years (15 years later). Those with an offer had about SEK 180,000 (about $26,000) at the same age later in life. The latter group's income is not far below national averages for the relevant age, whereas the former group's income is so low that it could hardly be collected from a full-time employment, albeit poorly paid. Unfortunately, the number of observations in the experimental study is in my opinion insufficient for any categorical claims. I therefore wonder if some one can offer an explanation to the result or point at other empirical studies in support of the seemingly extremely strong effect for this sub-group of girls? Details are in the attached manuscript.
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@John. The report that examined the boys is available by the attached link. It seemed that the boys worked more or less equally much in high school irresepctive of getting the random offer or not. Consequently, we did not try to further estimate the causal effect.
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We search for controls within a social experiment.
Our social experiment is made up of 9 areas and we are searching for similar areas. We use cluster analysis to find groups of areas and then look which group is the closest to our area. We cannot use propensity scores as logistic regression with a group containing one individual (or even 9) is not very adequate.
Do you know whether there are examples of the use of clustering for a similar work?
We also use synthetic control, but this technique implies that we would know the outcome of our research well before the end of the experiment.
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You could use the Mahalanobis distances between groups. A non-significant distance could be treated as zero. Sample size will influence this approach, so you could decide that a Mahalanobis distance less than "some value" will be sufficient to treat the two sets of data as coming from the same group. This would be from discriminant analysis.
Cluster analysis should also work. Look in the taxonomy literature where people are trying to work out the phylogenetic relationship between different species. The group (species) is made up of individuals, and you group them by both their similarities and differences. Entomologists do this sort of thing. Botanists used to do this, and may still. Usually the data in such studies is a combination of continuous and categorical variables. Continuous variables might be something like width of pronotum. Categorical variables might be something like number of spots on the elytra. Some key words would be cladistics, and numerical taxonomy.
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The ectomycorrhizic symbiose is very important for existing of many forest ecosystems like  Miombo woodlands. More mushrooms associated are edible.
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For the beginning you need to define a few things. You must choose a comparator (can be "do nothing"). You should choose outcome measure, perspective (societal, industry...) and time horizon.  But before all that, you must precisely define the research question. 
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I found that most checklists are used for  either model or trial-based economic evaluations. However, some checklists, like the one by Evers, 2005 seems to be model-based, yet classified as to be used for trial- based. Can someone please explain? Also, is it alright to use a model-based checklist for studies not model-based? 
Thanks!
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The first criteria list was published in 1974 by Alan Wiliam’s [1] and since that time there has been so much activity, you will find systematic reviews on the subject [2] and seems endless attempts to reach a consensus on the subject [3-4]. For general introduction, CRD have provided an good overview of assessing quality of economic evaluations [5]. The Drummond (BMJ) Checklist remains the most highly cited [6]
Choice of checklist depends on your specific question, the perspective you are coming from and types of economic evaluation.
If you wish to check ‘does this constitute an economic evaluation?’, the checklists mentioned already will confirm whether basic items required have been considered. For example, Drummond/BMJ or CHEC might initially screen the economic evaluation in a funding applications. Alternatively, CHEERS might be used to assess quality of reporting of pharmaco-economic evaluations.
However, if you wish to check ‘is this a reliable economic evaluation’ (so the objective is critical appraisal models), you should also note Cochrane Handbook, Chapter 15: Incorporating economics evidence, section 15.5.2 Critical appraisal of methodological quality [7]. Specifically for critical appraisals of decision-analytic models, the handbook has cited Philips checklist [8]. For modelling, of equal (or maybe greater) importance might be assessment of the quality of data inputs used for decision models; Cooper et al (2005) provide a useful framework using a hierarchical assessment to assess the quality of the data sources [9] .
References
  1. THE COST-BENEFIT APPROACH http://www.med.mcgill.ca/epidemiology/courses/EPIB654/Summer2010/CBA/CB%20approach%20Williams.pdf
  2. Walker, Damian G., et al. "Best practices for conducting economic evaluations in health care: A systematic review of quality assessment tools." (2012). http://effectivehealthcare.ahrq.gov/ehc/products/485/1302/MethodsBestPractices_FinalReport_20121023.pdf
  3. Evers, Silvia, et al. "Criteria list for assessment of methodological quality of economic evaluations: Consensus on Health Economic Criteria." International journal of technology assessment in health care 21.02 (2005): 240-245. http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=292673&fileId=S0266462305050324
  4. Husereau, Don, et al. "Consolidated health economic evaluation reporting standards (CHEERS) statement." BMC medicine 11.1 (2013): 80. http://www.biomedcentral.com/1741-7015/11/80 
  5. CRD's guidance for undertaking reviews in health care. Centre for Reviews and Dissemination, 2009. http://www.york.ac.uk/inst/crd/SysRev/!SSL!/WebHelp/5_5_QUALITY_ASSESSMENT.htm
  6. Drummond, M. F., and T. O. Jefferson. "Guidelines for authors and peer reviewers of economic submissions to the BMJ. The BMJ Economic Evaluation Working Party." BMJ: British Medical Journal 313.7052 (1996): 275. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2351717/ 
  7. Shemilt I, Mugford M, Byford S, Drummond M, Eisenstein E, Knapp M, Mallender J, McDaid D, Vale L, Walker D. Chapter 15: Incorporating economics evidence. In: Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions. Version 5.0.1 [updated September 2008]. The Cochrane Collaboration, 2008. Available at: http://hiv.cochrane.org/sites/hiv.cochrane.org/files/uploads/Ch15_Economics.pdf
  8. Philips Z, Ginnelly L, Sculpher M, Claxton K, Golder S, Riemsma R, et al.Review of guidelines for good practice in decision-analytic modelling in health technology assessment. Health Technol Assess 2004;8(36). http://www.journalslibrary.nihr.ac.uk/hta/volume-8/issue-36 , p.89-93
  9. Cooper, Nicola, et al. "Use of evidence in decision models: an appraisal of health technology assessments in the UK since 1997." Journal of health services research & policy 10.4 (2005): 245-250. http://hsr.sagepub.com/content/10/4/245.long
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I wanted to ask of some of the best conducted health economic evaluation studies for a research project. Thank you for your help!
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Any number of validated general health quality-of-life measures can be used to calculate the utility values that you will need for CEA. In addition to EQ-5D, SF-36 can be used, so can SF-12 (though this is not as robust for small sample sizes). Other newer instruments such as PROMIS-10 are also being used. All of these are "patient-reported outcomes measures", (PROMs). To my knowledge, disease-specific instruments cannot be used to calculate QALYs, though obviously they are useful for tracking clinical progress.
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I want to evaluate grain combine harvesters performance.
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thanks,very much
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We are currently conducting a systematic review on economic evaluation studies done in India. The results will be used to structure a benefit package design using CEA/CUA data from the selected full studies. We will be using guidance from WHO's document, "Making fair choices on the path to universal health coverage. Final report of the WHO Consultative Group on Equity and Universal Health Coverage".
If any of the members have experience of conducting such similar studies, do provide some inputs.
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Hi D. This is my view on the issue and a very short summary of what I have gathered from the literature and my experience. Benefit packages should be designed based on need and value for money. Defining need per se is quite complicated. Once you manage to define needs you might want to list the interventions that would meet those needs. Once you have the list of interventions that are candidate to be included into the benefit package you might have two problems. First, that there is more than one alternative to meet some needs. For example if hyperthension is an important need to be addressed you have alternatives, in this case different drugs are available. CEA would be useful to pick the drugs that are mos cost effective to meet the need of treating this condition. The second situation you might be facing is choosing between intervention for different conditions. Should we provide vaccines or treatment for chronic pulmonary disease. For answering that you would need CUA to have the chance to build league tables. You would also need a budget to know where in the league table you would cut. As I said, that is the theoretical part that is quiet hard to accomplish. Then you have all the politics around this issue that can turn the evidence based decision making package into a politically based package. Review the experience of Chile and their package called AUGE. It might be useful, specially how they dealt with the politics of that.
Hope this helps.
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What is believed to be the most important technique of impact evaluation for policy change or project intervention? Often researchers recommend the ‘before and after’ or ‘with and without’ intervention evaluation method by creating treatment and control group (or participant and non-participant in the project)? However, both methods have short comings of managing the attribution problems (what would have happened without the project?).
To address the attribution problem some researchers advise to you a simulation method; which is creating artificial control group from the treatment group.
Therefore, my question is how to construct this artificial group using multiple linear regressions; for instance, to assess the impact of microfinance intervention on poverty reduction?
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Read the following book: Evaluating the Impact of Development projects on Poverty by Judy L. Baker, World Bank, Washington D.C., May 2000
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I really don't have the background to know the ins-and-outs of this. I would really appreciate it if somebody could give me a critique of how plausible, usable, realistic, accurate this is and direct me to some hard-core research on the matter (or even newspaper/magazine articles!).
I realized there is a lot here, but a lot of it are casual conversations between a few people. Down the bottom the 'substance' of theory is discussed... may be complete nonsense or a con or it might well be enlightened thinking. I'd really appreciate it if you could help me. I feel it is plausible but not sure what questions I should be asking or where the holes are (and they might be gaping!).
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There is a conference on Collaborative Networks, called PRO-VE (link attached), you can find there the links to the proceedings. You can also take a look at the books written by Camarinha-matos.
If you're interested in the control/accounting aspects as well, you can take a look at this paper (link attached): "A review and discussion of management control in inter-firm relationships: Achievements and future directions" Ariela Caglio, Angelo Ditillo
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This will assist me in grasping and applying the concept of input-output models and social accounting matrices.
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About data:
There is a 1991 SAM for Zimbabwe:
GTAP has SAMs for a few other South African countries: https://www.gtap.agecon.purdue.edu/
The EORA database also reports tables for Zimbabwe (but to be honest I think the data is unreliable):
About research questions:
To find inspiration maybe you can browse the literature on African economics (e.g., http://jae.oxfordjournals.org/). Possible questions: the effect of market distortions such as energy and food subsidies; the effect of climate change; the effect of international aid; etc... People like Sherman Robinson and Channing Arndt have interesting studies about Mozambique, South Africa and other African countries. Specifically about Zimbabwe a quick Google search returned:
I hope this helps.
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Let me know if you have done research in the field of health promotion, more specifically its promotive actions. Are these actions cost-effective and do they show the value of health promotion?
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Sorry Paivi - I'm still 'none the wiser'. Most health promotion is important; it just depends on the relevance of its funding, evaluation, impact and dissemination.
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See critique of commodification of nature on
Forsaking Nature? Contesting ‘Biodiversity’ Through Competing Discourses of Sustainability’
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External cost like cost of CO2, health impact, etc. Also putting an economic value for these.
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Arif, Ecosystem impacts were one of the subjects of the 2005 ExternE methodology update which you can find at http://www.externe.info/externe_d7/sites/default/files/methup05a.pdf
It is also available on ResearchGate.
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I started being interested in the costs and benefits of patient participation in medical care. Is there any work in health economics showing that patient participation saves money (or not)?
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Dear Miriam,
There are some economic evaluations of 'Patient decision aids' which are specific methods for implementing shared decision making (Murray 2001, Kennedy 2003, Vourma 2004, Hollinghurst 2010). These analyses have measured, among other things, patient satisfaction, anxiety, quality of life and resource use. There is currently some work being done by Ara et al. from the University of Sheffield and University of York that might be helpful, http://www.eepru.org.uk/Shared-Decision-Making(2876643).htm
I hope this is helpful.
Sincerely,
Eldon Spackmkan
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Delivery of financing for research in public health between countries usually is determined by the GDP (low, middle and high income countries, classification created by the World Bank).
Shouldn't we employ another way to measure wellness? Human development index could be an option (if it was estimated in a uniform way across countries)?
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Could you specify the goal of your question? For instance, are you searching a metric for allocating resources? On top of this, one common measure of health outcomes in Health Economics is QALY (Quality Adjusted Life Years).
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Cost effectiveness analysis needs you evaluate cost first and probably more difficult, effectiveness of research? In complex situation you have to be simple, I just consider researchers’ production evaluated in number of publication in a major database. I work in life sciences domain, so my reference is PubMed.
In France, the national bureau of statistic INSEE produces an amount of spending in R&D each year at nation level and region by region. In 2008, each publication costs € 619 842 for the whole country. This figure has no sense in absolute value, namely because the gross national spending in R&D has a perimeter much larger than the PubMed domain. But the comparison of the figure from region to region should be valid.
I observe big differences between regions.
Paris and Lyon area are closed to the national mean, which is not surprising since around 60% of publications are localized here. But for Languedoc Roussillon (Montpellier, 4.7% of France ‘Publications) the cost is 799 691 €, 34 % over the mean and the other Mediterranean shore region, Provence, Alpes Cote d’Azur (Marseille and Nice area 8.4% of France ‘Publications ) is 561 550 €, -6% from the national mean.
I suspect a flaw, is someone has an idea?
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Many thanks for your stimulating interaction.
I am not statistician but just a pharmacist trains 40 years ago! I am not certain to understand all the issues in your comment. However, I understand that the natural variability of the data makes the difference non significant.
So I went back to raw data. I tabulate for the various regions the cost per publication year by year from 1999-2009, (the ten last years where the information is available).
As you can see the general trend is decreasing cost. Obviously, that is consequence of the famous “publish or perish”. With the same amount of money, they publish more since it is so important!
I send you In the attached file the data.
What your suggestion for a smart analysis?
Again, many thanks for your precious comments.