Science topic

Unemployment - Science topic

The state of not being engaged in a gainful occupation.
Questions related to Unemployment
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I want to design a study based on which the probability of unemployment in medical fields such as dentistry can be predicted in the future. What method is suitable for this and what models can I use? Can you recommend me a suitable book or article?
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Thanks
Mostly due to the increase in the number of dental students in recent years in Iran
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What is the role of local government units in terms of activating entrepreneurship and innovation, in terms of developing cooperation with local business, supporting the development of cooperation and clusters of companies cooperating with other entities, stimulating economic development in the municipal area, in the region?
In the context of the forecast decline in the economic activity of companies and enterprises in the coming quarters, the projected downturn in the national and regional economy, the decline in production and investment, the increase in unemployment and the current economic problems associated with high inflation, the importance of activating entrepreneurship and innovation of economic entities is growing. Within the framework of the interventionist, anti-crisis, Keynesian socio-economic policy, the government and central government agencies carry out programmes to activate entrepreneurship and innovativeness of economic entities, including companies and enterprises of the SME sector using specific financial instruments of fiscal, budgetary, sectoral policies, etc. On the other hand, a particularly important role in the activation of entrepreneurship and innovativeness of business entities of the SME sector operating in the area of the local economy of the municipality is also played by local government units. Local self-governments play an important role in terms of activating entrepreneurship and innovation, in terms of developing cooperation with local business, supporting the development of cooperation and clusters of companies cooperating with other entities, stimulating economic development in the area of the municipality, in the region. Effectively and efficiently conducted by local governments in this regard can significantly reduce the scale of downturn development in the local economy. When many units of local self-government efficiently activate economic processes, entrepreneurship and innovativeness, then the whole national economy goes through an economic crisis, recession, downturn more smoothly. As a result, the scale of the increase in unemployment and economic downturn is lower.
What do you think about this subject?
Please reply,
I invite you all to discuss,
Thank you very much,
Warm regards,
Dariusz Prokopowicz
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Role of local governments in the development and promotion of SMEs is a very interesting area for research and policy developments. Jorge Morales Pedraza the points you have raised are very relevant ones as well. Besides the seven points, the local governments also act as catalysts for promotion of innovations, especially, frugal innovations, which thereby enable the SMEs to explore commercial avenues for product development, marketing and trade, leading to value creation and and the well being of all those engaged into the SME related activities. The pandemic Coivd-19 give a further fillip to the local SMEs to expand their horizons with support from the local governments in many ways.
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When I tried to impute the data, the final table showed negative results for inflation and unemployment. How to go about it?
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Hans-Georg Petersen, I am conducting a study on the Indian States. For this, I required data on Inflation and Unemployment. The data is not consistent. When I tried imputation, the results for the missing value were negative, but that is not logical. I do not know the exact inflation and unemployment figures, but we are sure these were never negative in the given time frame. How to go about it?
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Continued high inflation for many more months, interest rates raised by the central bank, rising factor prices, falling consumption and investment will probably trigger a downturn in the economy in the following quarters and possibly also a significant rise in unemployment.
If such a scenario unfolds, could stagflation (high inflation and high unemployment at the same time) occur in 2023?
And if the risk of the emergence of stagflation in 2023 is high, what kind of anti-crisis socio-economic policy should the government apply to limit the scale of the economy's downturn?
What is your opinion on this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
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Quite possibly, if not in 2023 then in 2024.
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How can rising inflation be effectively contained?
On the one hand, the various instruments of monetary policy , fiscal policy, ... that have previously been used to stop the rise of inflation are known. On the other hand, for some reason the various anti-inflationary measures applied in 2021 and 2022 are working to a very limited extent. Therefore, can the rise in inflation get out of hand? Could the rise in inflation, the increase in fuel and energy prices and the projected downturn in the economy lead to the emergence of an economic crisis in the following quarters? Could there be an economic recession and stagflation in 2023?
What do you think on this subject?
Please reply,
I invite you all to discuss,
Thank you very much,
Greetings,
Dariusz
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Perhaps a novel way is to make stock exchange investment more alluring which will reduce consumption leading to a drop in inflation. This is what happened in Greece during the end of the 90's when everybody invested in stocks and inflation dragged down by a reduction in consumption pushed inflation from double digits to a level where it was possible for Greece to join the Eurozone.
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Dear All ;
Would you please recommend a theory or a previous studies
that can support my research.
Your support is highly appreciated.
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Dear Safa Nid,
There are two major theories that seek to explain the phenomenon of unemployment. For the first of them, of neoclassical inspiration, unemployment arises due to wage rigidity, caused by the behavior of agents (unions, companies, government) in the labor market. The second strand, derived from Keynes' General Theory, demonstrates that the level of employment fundamentally depends on the aggregate demand of the economy, which, in turn, derives from two variables: the propensity of the community to consume, which determines the level of aggregate consumption; and the current volume of investments.
The neoclassical conception that supply creates its own demand implied the premise that the savings generated by individuals, corresponding to the unconsumed part of their income, will necessarily result, in the same period, in an equivalent volume of capital investments. However, Keynes warned that, in the real world, the individuals who save are not necessarily the same individuals who make the decisions to invest in new machinery, equipment, or to establish new businesses. The amount of current investment depends on what Keynes called the incentive to invest, which in turn is linked to the relationship between entrepreneurs' expectations of future market behavior and the level of interest rates.
Then, given the marginal propensity to consume, entrepreneurs will increase or decrease employment, through the level of investment. The investment incentive depends on the relationship between the marginal efficiency of capital and loan interest rates. Thus, there can only be one level of employment compatible with the equilibrium: Income = Consumption + Investment. Otherwise, global demand and global supply would be different. This level of employment may be below, but not above, full employment. This fact attests to the mutual relationship between the marginal propensity to consume and the incentives to invest. In view of this aspect, the level of employment is determined by the marginal propensity to consume plus investment, which also determines the level of real wages. If the marginal propensity to consume and the amount of investment result in insufficient effective demand, the volume of employment falls until it is below the supply of labor willing to work at the prevailing real wage. This leads to involuntary unemployment.
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What is technology unemployment and how can it be addressed?
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Technological unemployment occurs when one loses his job because of new technological development and change.
In this new situation, the existing employed manpower lacks new knowledge and skills created for technical or technological development, and they are bound to lose their jobs.
It can be addressed through technology integration. Students should be encouraged to use e-contents to improve learning, access e-resources for studying, and use information technology for academic preparation and problem solving. Continuous on-the-job training should be arranged for young and skilled manpower. The government should take an effective policy to reduce technological unemployment. Besides this, the traditional sectors like agriculture should also be a prior concern for all countries to address technological unemployment.
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Dear colleagues, I am conducting a quasi experimental analysis focused on the Italian labor market. More specifically, I would like to evaluate the impact of a specific reform over the probability (after some specific time period, e.g., 1 year) of being employed (or not) after the implementation of the reform. Therefore, the outcome variabile is a dichotomous variable equal to 1 if the individual is employed after the specific time period, 0 if not. In the literature, as far as I know, quasi-experimental studies are conducted using mainly continuous response variables. My idea is to rely on a Propensity Score Matching (PSM) approach. However, I would like to ask you for some suggestions and works to consult in order to properly undertake this analysis of mine. Thank you in advance.
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I would do a survey using Likert scales and analyse with Chi Square tests :)
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I am looking for the most workable recommendation(s) on how African countries can effectively combat the monkeypox disease which is gradually becoming a canker. Please bear in mind that most of these countries are HIPCs with massive problems of poverty and unemployment.
What do you suggest?
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Thank you Sir,
My study seeks to explore plausible means by which African countries can effectively combat the monkeypox disease amidst contemporary global socioeconomic challenges posed by the COVID pandemic and the Russia-Ukraine war.
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For my research, I am unsure whether I can convert these variables to LN or not as different papers suggest different things.
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@T.bh the essence of taking the log form is to reduce the magnitudes and bring to par with other variables in the model.
For the variables mentioned, they're already rates and therefore similar in form. You therefore do not need to transform them. If you have other variables in your model that are not in rates, you can only transform such to maintain similarities with the aforementioned.
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I need help to know which trend specification to use from the options of none, restricted constant, unrestricted constant, restricted trend or unrestricted constant and trend. The research is on the impact of financial development indicators on unemployment.
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I think you can plot the data of both the explained and the explanatory variable to see if they follow a particular pattern. This will inform your choice of trend specification to use.
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This question is very important to develop a plan and strategy to confront the problem of unemployment that is increasing among young people in society In all countries of the world ?
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School curricula should take the needs of the job market into account. Therefore, it is extremely important that students build their capacity in job creation.
Thus, they should learn to be creative and innovative at early age.
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One of the outstanding features of recoveries from the 1990-91, 2001 and 2007-09 recessions was the mild recoveries from each. Except for the boom of the late nineties when real GDP grew between 4 and 5 % (1997-2000), real GDP between 1992 and 2019 grew at annual rate of less than 4 % each year. During the 28 year period from 1992 to 2020 inflation, except for a brief period in 2005-06, generally fell in the 1 to 3 % range, which had not been the case for the quarter century 1967-1991. While other factors, no doubt, also contributed to very low inflation, surely the weak recoveries were an important factor tending to mitigate inflationary pressure. This was especially true of the decade of tepid recovery after the Great Recession of 2007-09. The unemployment rate peaked at 9.5% in both 2009 (the cyclical trough) and 2010, and still averaged about 8% in 2012. In contrast, unemployment peaked during April 2020 at 14.7% for the Covid Contraction and fell very quickly -- about1% per month in 2020 so that by December of that year that rate had plummeted to 6.7% and it would sink further to 3.6% by early 2022. It would seem that the sharp monetary and fiscal stimulus that contributed to the strong and rapid recovery from the 2020 recession, among other factors, such as covid-induced supply side issues, contributed to reflation that has seen the U.S. CPI to rises at annual rate of 8.5% by early 2022.
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Yes, the silver lining of the weak recoveries of the three US recessions between 1990 and 2010 was very low inflation.
Bernanke argued that central banks’ focus on anchoring expectations has been the “most important factor over the long haul” in the behavior of price inflation.
Changes in the global economy may have suppressed inflation in the U.S. even while unemployment has been declining; globalization not only has direct immediate effects on inflation but does affect the Phillips Curve. Shifts in the industrial composition of the economy complicate the use of traditional inflation statistics. The Fed is currently in the process of reviewing its monetary policy framework.
With respect to the 1990s, some statistical observations are in this link:
Inflation is not about general increases in prices as such, but about the increase in the money supply. As a rule, the increase in the money supply sets in motion general increases in prices. The economic effect of money that was created out of thin air is the same as that of counterfeit money — it impoverishes wealth generators. The money created out of thin air diverts real wealth toward the holders of new money.
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Mild steady inflation cannot help—it can lead only to outright inflation. That inflation at a constant rate soon ceases to have any stimulating effect, and in the end merely leaves us with a backlog of delayed adaptations, is the conclusive argument against the "mild" inflation represented as beneficial even in standard economics textbooks.“ —  Friedrich Hayek
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Some developing countries with a striving informal economy have low unemployment and high GDP. In contrast, others with a smaller percentage of the informal economy have very high unemployment levels and low GDP.
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Dear Prof Prakasam
Thanks a lot for providing good answer to this question. Your support is greatly appreciated.
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Looking for evidence that this has broader reaching causal effects on the economy.
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High unemployment indicates the economy is operating below full capacity and is inefficient; this will lead to lower output and incomes. The unemployed are also unable to purchase as many goods, so will contribute to lower spending and lower output. A rise in unemployment can cause a negative multiplier effect.
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What theory can be use to model poverty, unemployment, inequality and economic growth?
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Hi there,
I am trying to build an ARDL model to predict recessions in the US using industry productivity, the difference in yields between 3 month and 10 year treasury bills, unemployment rate and the federal rate. The recession variable is a binary variable with a value of either 0 or 1. Is it correct to just lag the variables and use a probit function to regress recession on these variables or is that not a valid approach? When I do just do that and then try training my model and forecasting periods for which I have data, my model fits too well. It sits at almost 0 for most of the time (well more accurately it sits at numbers such as 5.18e-18) with the occasional one period spike and then jumps to something like 0.9997 when there was a recession.
My code looks like this:
probit rec l(1).rec l(4/6)d.m3 l(4/8)d.unr l(6/12).indprod l(3/5).fedr if tin(1985m1, 2003m1)
predict rec_hat if tin(2003m2, 2020m2)
tsline rec rec_hat if tin(2003m2, 2020m2)
Note the lag periods are not optimised (but I don't want to ask too many questions on one post), but the time plot created is robust to many different specifications.
I know it seems strange to have a model which is too good, but I know there has to be something wrong for it to be forecasting so accurately. In no period should there be 0 chance or 100% chance of recession.
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thank you so much professor
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At present, the economies of developed countries are entering the period of the fourth technological revolution known as Industry 4.0.
The previous three technological revolutions:
1. The industrial revolution of the eighteenth and nineteenth centuries, determined mainly by the industrial application of the invention of a steam engine.
2. Electricity era of the late nineteenth century and early twentieth century.
3. The IT revolution of the second half of the twentieth century determined by computerization, computerization, the widespread use of the Internet and the beginning of the development of robotization.
The current fourth technological revolution, known as Industry 4.0, is motivated by the development of the following factors:
- artificial intelligence,
- cloud computing,
- machine learning,
- Big Data database technologies,
- Internet of Things.
In every previous technological revolution, the same question was repeated many times. However, economies developed and changed structurally and labor markets returned to balance. Periodically, short-term economic crises appeared, but their negative economic effects, such as falling income and rising unemployment, were quickly reduced by active state intervention.
It seems to me that self-malting and robotization, IT, artificial intelligence, learning machines will change the labor markets, but this does not necessarily mean a large increase in unemployment. New professions, occupations, specialties in these areas of knowledge and technology will be created. Someone, after all, these machines, robots, etc. must design, create, test, control, and implement into production processes.
Therefore, I am asking you:
Will the technological development based on self-mulization, robotization, IT development, artificial intelligence, machine learning increase unemployment in the future?
Please reply. I invite you to the discussion
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Dariusz Prokopowicz What you stated is true; everytime there is technology revolution; there is hugh fear of unemployment. What I believe it that all above technologies would great new employment opportunities; however challenge this time would be for human workforce to come upto speed with transition. Since with the combination of AI, Robotics, IOT and so forth; solution development life cycle would be shortened; and new solutions would come up in much shorter timeframe; makes sure that existing once soon become legacy. So we as humans will have to buckle up and also prepare our future generations!
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moreover I want to know that along with described time series Variable, discrete variable can be included in the model.
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6 points about that:
1) You can use discrete variables, for example, dummys with a value of 1 in certain years and zero in others.
2) Sometimes, the use of the log reduces the problems caused by heteroskedasticity (for example, if the size of the errors are associated with the level of the variables studied).
3) In addition, you can use the log in models that intend to evaluate growth rates, since the differences in the logs show an approximation of the rates.
4) Variables that are already rates are not usually logged, but you can create log(1+rate) if you wish.
5) Variables defined by ratios [w=x/z] can be placed in log or not, depending on the relations between y, x and z that you want to study. In a regression model with dependent variables in log it is more common to write y = a + b*log(x) +c*log(z) + error or log(y) = a + b*log(x) +c*log(z) + error. Depending on what you want.
6) However, it is common to use ratios as dependent variables. In these cases, they may or may not be in log: y=h/s or log(y) = log(1+r) can be used as a dependent variable, where r = (h-s)/s.
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I am a student of BBA. I want to do my research project on FDI in Bangladesh. As unemployment is a severe problem in our country, foreign direct investment can play a significant role.
What could be the relationship between FDI and unemployment in the context of developing country.
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1 percent increase in FDI raises employment growth by about 3 percent and exports by almost 9 percent, concluding that FDI tends to provide an outlet for surplus productive capacity and labour in the receiving country. Which is why FDI can play a significant role.
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It is shocking that we let immigrant/refugee children in our countries and then do not pro-actively adress the widely-known challenge they may face: low avademic achievement thats leads to drop out from school that leads to unemployment. Please provide your valuable suggestion on how to solve this. Thank you.
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Effective practices include: establishing direct lines of communication with students and families in English and other languages spoken at home; partnering with immigrant-serving community organizations to inform families about their rights and options; involving bilingual family resource center staff, family liaisons ...
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Is it ethical to develop artificial intelligence, robots, and automation technologies that result in the loss of jobs for humans?
Please express your thoughts.
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A very suggestive and interesting question. Indeed, today we live in the age of technology, but I must say one thing: I believe that robots created by thousands cannot do the work that one person can do with their emotions. Because no robot can fulfill the love and affection of a person for the profession. As you mentioned in your question about this, thanks to the creation of robots, unemployment is sure to rise.
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Hi, I'm to do a multivariate regression analysis using TSCS data in R, and I'm a bit lost as to where I should start. My research question is how ALMP's have affected unemployment in four European countries over a 20 year time period, using expenditure data on subprograms from OECD. The resources I have from class don't show how to do a TSCS analysis so I'm wondering if people have tips on where I should start and what to do.
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Unemployment is the dependent variable and ALMP's are the independent variables... Try to execute a simple regression model on R then Interprete how the independent variable affects the dependent variable.
Best!!
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A significant increase in inflation as an important factor in the possibility of a possible new economic crisis?
What are the main sources of the increase in inflation in your country?
Can the rise in inflation in the coming months lead to specific economic problems for enterprises?
Is the increase in inflation in 2021 one of the major economic problems in your country, or is it a potential cause of these problems?
Are there symptoms of a much more serious problem, ie stagflation (high inflation and high unemployment, low economic growth)?
How can entrepreneurship be activated in a situation of stagflation following the economic crisis of 2020 caused by the SARS-CoV-2 (Covid-19) coronavirus pandemic and still relatively low interest rates?
In this discussion, please answer the above questions.
I invite you to discuss this issue.
What do you think about this topic?
What is your opinion on this issue?
Please reply,
I described a strong increase in inflation as a result of the applied interventionist state aid programs offered on a historically record scale to commercially operating economic entities in my article published at the end of December 2021. I am providing a link to this article:
I invite you to research cooperation in the field of developing new concepts for planning and implementing an effective strategy for the socio-economic development of the country, including shaping the anti-crisis and pro-development socio-economic policy in such a way as not to cause an increase in inflation, an increase in public debt and other negative effects of incorrectly conducted economic policy.
Thank you very much,
Best regards,
Dariusz Prokopowicz
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I think that all countries suffer from this inflation, since there is a huge imbalance in the economic principles of supply and demand but also as a result of the devaluation of currencies. However, the situation will normalize very soon since this inflation is the consequence of Covid-19.
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The question is about contributions of research methods that help to unravel or tackle social or political issues in Ghana
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You are looking at the wrong end of the telescope. What are the research questions that you are trying to answer? Given that, what are the appropriate methods?
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Such as keeping power plants in operation despite falling profits to ensure capacity adequacy, or because of concerns relating to unemployment, etc.
Any article or other information about this phenomenon is very much appreciated!
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I don't know about utilities, but there is some literature on the use of national oil companies for all kinds of purposes. In many developing countries this has led to lack of clarity about tasks and responsibility, all kinds of inefficiencies and corruption, the NOC becoming a state in the state etc. Unfortunately I can't remember concrete publications, but if you search for literature on national oil companies, it should be possible to find something.
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I am a master's student in Japan.
My study focuses on the youth unemployment rate in Sri Lanka.
I want to analyze the impact of the employment promotion policies of the Sri Lankan government and ILO in the labor market on the youth unemployment rate in Sri Lanka.
I want to use DD & RDD analysis as an analytical method for this purpose.
Which papers should I read to conduct the above kind of analysis?
I also would like to know if there are any papers on DD & RDD analysis that I should read.
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A rgression discontunity design(RDD) is equuasi_ expermintal pretest_posttest design that aims to determine the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention assigned. Two most common approachs to estimate using an RDD are non_ parametric and parametric ( normally polnormaial regression). Mor detailed illustrated in the attsched ref:
https://en.mwikipedin.org.>wiki
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Robotization is clearly accelerating its pace. Does it have the potential to bring immediate unemployment? What are its advantages for Human Resources?
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The technological progress in robotization is one of the key elements of the current fourth technological revolution and the development of Industry 4.0 technology. Robots equipped with artificial intelligence can be employed in companies and enterprises in workplaces where frequently repetitive tasks are performed. On the other hand, in workplaces that require innovation, artistry, creating unconventional solutions, creativity, etc., robots should not replace people.
Regards,
Dariusz Prokopowicz
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Good afternoon,
I want to ask, can anybody tell me the website/link for finding out the daily data on inflation rate and unemployment rate in India. Please share your knowledge and experience. I will be very thankful to you.
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Yes exactly. I find data on monthly, quarterly basis on different websites. But in my base paper, all the data was taken on daily basis. As per that paper, they have extracted data from Yahoo finance and investing.com. But I am unable to find daily date there also.
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Although, he initially estimated the relationship in 52 years, isn't that long enough for it to be at the naural rate of unemployment or NAIRU? If not, how long does it take for it to become so?
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When the data is collected over a long period of time, the curve derived is a long-run overall picture. However, the application, i.e. using the curve as a predictive function, is always short-run. To use such a function (curve) for longer forecast horizon the accuracy becomes less and less accurate. Therefore, what can be said about the use of such curve is couched in the language of short-run. The curve is a long-run picture but it's use should always be short-run. In the long-run, the controlling variable may change and the prediction becomes less accurate.
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Hello everyone,
I am looking for the best possible source to get the data on unemployment specifically in Hospitality/Tourism Industry which is worse hit due to Covid-19.
it is for a project purpose. any researcher can please provide insight on source stat.
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It will really be somewhat DIFFICULT since, obviously, it will depend on each Country, its System, Structure and Economic Strength and, of course, the TRANSPARENCY AND TRUTH OF EACH COUNTRY WHEN PROVIDING SUCH DATA (if offered): It is likely that the Organization Internacional del Trabajo (ILO)) have information about it ... then look on their website (www.ilo.org)
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I am working on a paper on unemployment on psychological health of youth. Please in what order can input the following predictors variables using age as the control variable?
Perseverance
Irrational behaviour
Low self esteem
Depression and
Suicidal ideation
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It probably depends on your hypotheses and your design. I'd look at inter correlations between them, to see if multicollinearity might become a problem, but in the end theory and predictions should dictate the order.
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COVID-19 pandemic shut down many Universities and businesses around the world. Millions of peoples lost their job. Some companies asked their employees to work from home, and universities offer online teaching, a new experience for many. How all of these going to play out with the future of education?
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In my view, University is decreasing income during pandemic covid 19
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COVID 19 pandemic has shaken the roots of World in all aspects. Infections, Deaths, inability to create facilities, stress upon front-line workers, restrictions and unusual adaptation in life-style, lockdowns and economic down-turn, loss of job and income, unemployment, limited establishments, insecurity and so on.. Luckily, now vaccines are rolling all over the world. Since the viral strain is continuously mutating and increasing its virulency, I need to know what impact does the vaccine administration will have upon the virus. Will it become more virulent or benign in the coming days?
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Despite the administration of potent COVID 19 Vaccines, other measures of preventing the spread must not be discarded.
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Hello. I'm a second year undergraduate undertaking a mini research project on the effect of unemployment on the probability of getting divorced. I'm using data from the British Household Panel Survey (18 waves). I have attached my regression below.
From the literature, I have seen that the impact of unemployment on divorce is much more significant for men compared to women, so I was wondering whether it would be a good idea to add interaction terms between the dummy variable "sex" and my unemployment variables to capture this effect.
Also, I'm unsure whether a probit or a logit model would be most suitable, as in the literature I have seen both used.
Finally, I don't know whether to use fixed effects or first differences estimator.
Any help would be much appreciated.
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I can't see any regression attached below
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Let suppose, if COVID's second wave will hit then what will be the consequnces in terms of global economy? what will be the standing of real state sector and level of unemployment and inflation in future?
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I think the economic impact of this pandemic will be quite significant. For the time being, no country seems to have a clear recovery strategy.
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Unemployment has become a common problem in almost every developing nation. Jobs are not there in order to provide a source of livelihood to all. So, it becomes essential that one should do some other activity, one such option is to enter the field of Dairy Farming.
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It’s true that young enthusiast people should be more enterprising and less dependent on traditional trend to only try to get a job to have a livelihood.
Dairy farming, no doubt, is a good option as a start up business investment. Both milk and related products like cheese, butter, etc have good prospect and are positive products to produce as these are products which contribute towards overall social wellbeing of mass population of any country. Moreover, dairy value chain has still have ample scope to add have to it and one can contribute through dairy farming in an appropriate manner.
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Architectural and economic aspects are important. But beyond that, challenges and solutions need to be addressed comprehensively and viewed holistically in the new city model. Reducing inequality and achieving sustainability are two objectives that should be pursued, but the challenges will vary depending on each city and its degree of development. In European cities, the situation may not be as dramatic as it is in emerging countries, but this could change as a result of various factors, such as the aging of the population, the influx of refugees of war or natural disasters, and unemployment. Therefore, a key aim in Europe is to ensure that large cities are engines of sustainable economic growth where particular population segments—such as young people—can find work, whereas the goal in developing countries such as Brazil, Colombia, and India is to provide housing and basic services for all social classes. This aspect is very important not only from the standpoint of housing but also for governance and city strategy.
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Cities of the future should be a socially diverse environment where economic and social activities overlap and where communities are focused around neighborhoods. They must be developed or adapted to enable their citizens to be socioeconomically creative and productive. Recent developments provide hope that such challenges can be tackled. Kindly the following RG link:
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I have been through a number of journals and Research Papers. I wanted to get an idea as to what new areas are still left to be researched in "Will Automation lead to unemployment or it will lead to skill enhancement to survive in the labor market ".
Please suggest accordingly so that I can proceed. I am a novice learner and some help would be appreciative.
Thanks in advance.
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Dear Indira Roy , thank you very much for your interesting question.
Far from being an expert on the subject, I take the liberty of adding some notions linked to this relationship.
Among the authors who disbelieve in the self-regulation of markets, there is a consensus on the deterioration of the labour market, associated with structural transformation policies - asymmetries between the economic and the social, flexibility of labour relations, the level of the minimum wage in collective bargaining, training and employment insurance, etc. -.
The labour market literature is often too divergent with regard to the functioning of the labour market. The solutions to unemployment of the main theories are far from consensus. One could mention the neoclassical paradigm, where labour market imbalances are solved by relative price adjustment, self-regulating as in any other market, on the one hand. On the other hand, the concept of unemployment in the modern sense, which only came about at the beginning of the 20th century (Salazar, 2011). It is understood as an involuntary phenomenon (Webb and Webb, 1909), and of a social nature, caused by the malfunctioning of the labour market, which requires state action for its solution (Beveridge, 1930). Although the latter explanation gains more emphasis with Keynes.
There is a long-standing paradoxical relationship between technical progress - the coincidence of the advance of automation, among other technological advances - and employment. Regarding this complex link, Ricardo wrote: "I am convinced that the substitution of machines for human labour is often detrimental to the interests of the working class (...)" (Ricardo, 1817, p. 344). In the same vein, Marx predicted that the process of mechanisation would condemn workers to subsistence wages (Marx, 1906), while Keynes expressed himself using the concept of "technological unemployment" (Keynes, 1963), while Leontief stated that "the role of humans as the most important factor of production is bound to diminish (...)" (Leontief, 1983, p.3). In the 1960s, fears were expressed of an extreme scenario - the Technological Singularity - where intelligent machines would become more and more powerful, overtaking humans and pushing them out of the labour market. As a consequence, wealth and power would be concentrated in the hands of a small elite of owners, creating unprecedented inequality (Harari, 2017). Today, some pessimistic authors, such as Beck (1998), argue that the new productivity law of global capitalism in the information age implies less educated and globally interchangeable workers. Meanwhile, Frey and Osborne estimate that 47% of jobs in the United States may disappear (Frey and Osborne, 2017). In contrast, Joel Mokyr, rejecting the positions of the "technopessimists", believes that the future will bring occupations that will be as foreign to us as many of today's jobs are to our grandparents (Mokyr, 2014).
The evidence of recent years is a very heterogeneous labour market - by industries, occupations and countries - and a strong polarisation of work. On the one hand, the collaborative economy and the emergence of digital platforms are generating a dizzying growth of part-time and real-time contracting, self-employment (Salinas, 2001), with minimal social protection - and low job quality - and detached from labour legislation (Tirole, 2017). These markets demand greater flexibility and the ability to adapt to new skills - as opposed to the professional profile or over-specialisation of the past (Bessen, 2015). On the other hand, the differentiation between routine and non-routine tasks characterises the current period. The former, whether skilled or unskilled, can easily be robotised. Thus, the diversification of training objectives, compatible with a versatile workforce, goes beyond mere job matching (Farber, 1993), and is increasingly framed within the framework of continuing education for employment (Salinas, 2001).
Against the backdrop of the COVID-19 pandemic crisis, which leads to a shutdown of economies and societies are in more or less severe quarantines, measures comparable only to those in wartime situations, we face an uncontrolled rise in unemployment. The ILO estimates that there are between 5.3 million ("cautious" scenario) and 24.7 million ("extreme" scenario) new unemployed from a baseline of 188 million unemployed in 2019 globally - the 19.4 million unemployment gap in the prediction reflects the difficulty of the COVID 19 health crisis. For comparison, the 2008 global financial crisis increased the number of unemployed by 22 million. In addition, the agency highlights that 1.25 billion workers are at risk of layoffs, reduced wages and possible reduction in hours worked. According to the estimates of international agencies, the current health crisis will adversely affect the world of work in three key ways:
Increased unemployment and underemployment; 2. Job precariousness - with respect to wages and access to social protection; and 3. Effects on the most vulnerable specific groups - these tend to be women, young people and immigrants who have a more precarious employment situation linked to temporariness, and less skilled jobs developing elementary occupations that cannot be adapted to teleworking.
It is no easy task to predict the impacts of the technologies of the digital world - robotisation, hyperconnectivity, artificial intelligence, among others - on the future labour market. In a context where there is no consensus on slowing down the speed of automation for a better adaptation and a reduction of its negative consequences, it is no easy task to predict the impacts of the technologies of the digital world - robotisation, hyperconnectivity, artificial intelligence, among others - on the future labour market. Given the multiplicity of factors that mediate between technological development and unemployment, I would like to know more about the state of knowledge of the issues mentioned.
I apologise Indira Roy for the general nature of this reply. We look forward to the contributions of more colleagues who are working on these issues, in order to sort out the ideas.
Best regards and thanks
Fernando (from Argentina)
Bibliography:
Bessen, J., (2015). Learning by doing: The real connection between innovation, wages and wealth, Yale University Press
Beveridge, W.H. (1930). Unemployement. A problem of industry. Londres, Longman.
CEPAL (2020), COVID-19 tendrá graves efectos sobre la economía mundial e impactará a los países de América Latina y el Caribe.
CEPAL, N. (2020). América Latina y el Caribe ante la pandemia del COVID-19: efectos económicos y sociales.
Farber, H. S. (1993). The incidence and cost of job loss: 1982-91. Brooking Papers on Economic Activity, 1, 73- 132.
Frey, C.B. y Osborne, M., (2017). “The future of Employment: How susceptible are Jobs to computerisation”, Technological Forecasting and Social Change, 2017, vol. 114, issue C, 254-280.
Harari, Y., (2017). “Homo Deus”, Taurus.
Keynes, J.M., (1963). Essays in persuasion, Norton. Versión en castellano: Ensayos de persuasión, Editorial Síntesis, 2009.
Leontief, W., (1983). “National perspective: The definition of problems and opportunities”, en National Academies: The long term impact of technology on employment and unemployment, National Academy of Engineering.
Marx, K., (1906). Capital: A critique of political economy, Modern Library, Nueva York, pgs. 708- 709.
Mokyr, J., (2014). “Secular stagnation: Not in your life”, VoxEU, Agosto.
OIT, (2020). “Covid-19 y el mundo del trabajo: repercusiones y respuestas”, 18 de marzo de 2020
OIT, (2020). World employment and social outlook – Trends 2020.
OIT, (2020). Young workers will be hit hard by COVID-19’s economic fallout.
Salazar, O. C. (2011). La precarización laboral y el desempleo como consecuencias del neoliberalismo y la globalización. Revista Tendencias & Retos, (16), 43-57.
Salinas, J., (2001). “TIC: ocupación y formación ¿globalización-desempleo?”. Artículo presentado en CIFO III Congreso de Formación Profesional ocupacional. Formación, trabajo y certificación, realizado del 20 al 23 junio del 2001.
Tirole, J., (2017). La economía del bien común, Taurus.
Webb, B. T Webb, S. (1909). The break-up of the poor laws, Londres, Fabian Society, 1909.
Estimada Indira, muchas gracias por tu interesante pregunta
Lejos de ser un experto en el tema, me tomo el atrevimiento de sumar algunas nociones vinculadas a esta relación.
Entre los autores que descreen de la autorregulación de los mercados, se destaca el consenso en el deterioro registrado en el mercado de trabajo, asociado a políticas de transformación estructural – asimetrías entre lo económico y lo social, flexibilidad de las relaciones laborales, nivel del salario mínimo en las negociaciones colectivas, seguro de capacitación y empleo, etc.–
La bibliografía respecto al mercado de trabajo suele ser demasiado divergente respecto al funcionamiento del mercado de trabajo. Las soluciones al desempleo de las principales teorías están lejos del consenso. Podría mencionarse el paradigma neoclásico, en donde los desequilibrios del mercado de trabajo se resuelven mediante un ajuste de precios relativos, autorregulándose como sucede en cualquier otro mercado, por un lado. Y el concepto de desempleo en sentido moderno que se produce recién a principios del siglo XX (Salazar, 2011), por otro. Entendido como fenómeno involuntario (Webb y Webb, 1909), y de carácter social, causado por el mal funcionamiento del mercado de trabajo, que requiere la acción del Estado para su solución (Beveridge, 1930). Si bien esta última explicación cobra mayor énfasis con Keynes.
Existe una paradójica relación de larga data entre el progreso técnico –incidencia del avance de la automatización, entre otros avances tecnológicos–, y el empleo. Respecto a este vínculo complejo, Ricardo escribía: “Estoy convencido de que la sustitución del trabajo humano por las máquinas es con frecuencia perjudicial para los intereses de la clase trabajadora (...)” (Ricardo, 1817, p. 344). En el mismo sentido, Marx predijo que el proceso de mecanización condenaría a los trabajadores a salarios de subsistencia (Marx, 1906), en tanto, Keynes se manifestó utilizando el concepto de “desempleo tecnológico” (Keynes, 1963), mientras que Leontief afirmo que “el papel de los humanos como el factor de producción más importante está llamado a disminuir (…)” (Leontief, 1983, p.3). En los años sesenta se expresó el temor por un escenario extremo –la Singularidad Tecnológica–, en donde las máquinas inteligentes se harían cada vez más potentes, llegando a superar al ser humano, expulsándolo del mercado de trabajo. Como consecuencia, la riqueza y el poder se concentrarían en una pequeña élite de propietarios, creando una desigualdad sin precedentes (Harari, 2017). En la actualidad, algunos autores pesimistas como Beck (1998), manifiestan que la nueva ley de productividad del capitalismo global en la era de la información, implica trabajadores menos formados y globalmente intercambiables. En tanto, Frey y Osborne estiman que un 47% de los empleos en Estados Unidos pueden desaparecer (Frey y Osborne, 2017). En cambio, Joel Mokyr en rechazo a las posturas de los “tecnopesimistas”, considera que el futuro traerá ocupaciones que nos resultarán tan extrañas como muchas de las actuales a nuestros abuelos (Mokyr, 2014).
La evidencia de los últimos años, es un mercado laboral muy heterogéneo –por industrias, ocupaciones y países–, y una fuerte polarización del trabajo. Por un lado, la economía colaborativa y la aparición de plataformas digitales está generando un crecimiento vertiginoso de contrataciones de trabajo parcial y en tiempo real, empleo por cuenta propia (Salinas, 2001), con mínima protección social – y baja calidad de empleos–, desvinculadas de las legislaciones laborales (Tirole, 2017). Estos mercados demandan mayor flexibilidad y capacidad de adaptarse a nuevas competencias –a diferencia del perfil profesional o la sobreespecialización del pasado (Bessen, 2015) –. Por otro lado, la diferenciación entre tareas rutinarias y no rutinarias caracterizan al periodo actual. Las primeras, requieran cualificación o no, se pueden robotizar con facilidad. De manera que la diversificación de los objetivos formativos compatible con una fuerza de trabajo versátil, supera la mera adecuación al puesto de trabajo (Farber, 1993), y se enmarcan cada vez más en una educación continua para el empleo (Salinas, 2001).
Ante la coyuntura de la crisis de la pandemia del COVID-19, que conduce a un cierre de las economías y las sociedades se encuentran en cuarentenas más o menos severas, medidas solo comparables a las de situaciones de guerra, enfrentamos un descontrolado aumento del desempleo. La OIT estima que hay entre 5,3 millones (hipótesis “prudente”) y 24,7 millones (hipótesis “extrema”) nuevos desocupados a partir de un nivel de base de 188 millones de desocupados en 2019 a nivel mundial –la brecha de 19,4 millones de desocupados en la predicción refleja la dificultad de la crisis sanitaria del COVID 19–. Para establecer una comparación, la crisis financiera mundial de 2008 aumento la cantidad de desocupados en 22 millones. Además, el organismo resalta que 1,25 billones de trabajadores se encuentran en riesgo de despido, reducción del salario y posible disminución de horas trabajadas. Según las estimaciones de los organismos internacionales, la actual crisis sanitaria repercutirá adversamente en el mundo del trabajo en tres aspectos fundamentales:
1. Aumento del desempleo y del subempleo; 2. Precarización laboral –con respecto a los salarios y el acceso a protección social–; y 3. Efectos en los grupos específicos más vulnerables–suelen ser las mujeres, los jóvenes y los inmigrantes que poseen una situación laboral más precaria vinculada con la temporalidad, y los empleos menos cualificados que desarrollan ocupaciones elementales que no pueden adaptarse al teletrabajo.
No es tarea sencilla predecir los impactos de las tecnologías del mundo digital – la robotización, la hiperconectividad, la inteligencia artificial, entre otros–, en el mercado laboral futuro. En un contexto en que no existe consenso en reducir la velocidad de la automatización, para una mejor adaptación, y una disminución de sus consecuencias negativas. Dada la multiplicidad de factores que median entre el desarrollo tecnológico y el desempleo, desearía conocer con mayor profundidad el estado del conocimiento de las problemáticas mencionadas.
Le pido disculpas Indira por el carácter general de la respuesta. Esperamos los aportes de más colegas que están trabajando estos temas, para que ordenen las ideas.
Un saludo y gracias
Fernando (desde Argentina)
Bibliografía:
Bessen, J., (2015). Learning by doing: The real connection between innovation, wages and wealth, Yale University Press
Beveridge, W.H. (1930). Unemployement. A problem of industry. Londres, Longman.
CEPAL (2020), COVID-19 tendrá graves efectos sobre la economía mundial e impactará a los países de América Latina y el Caribe.
CEPAL, N. (2020). América Latina y el Caribe ante la pandemia del COVID-19: efectos económicos y sociales.
Farber, H. S. (1993). The incidence and cost of job loss: 1982-91. Brooking Papers on Economic Activity, 1, 73- 132.
Frey, C.B. y Osborne, M., (2017). “The future of Employment: How susceptible are Jobs to computerisation”, Technological Forecasting and Social Change, 2017, vol. 114, issue C, 254-280.
Harari, Y., (2017). “Homo Deus”, Taurus.
Keynes, J.M., (1963). Essays in persuasion, Norton. Versión en castellano: Ensayos de persuasión, Editorial Síntesis, 2009.
Leontief, W., (1983). “National perspective: The definition of problems and opportunities”, en National Academies: The long term impact of technology on employment and unemployment, National Academy of Engineering.
Marx, K., (1906). Capital: A critique of political economy, Modern Library, Nueva York, pgs. 708- 709.
Mokyr, J., (2014). “Secular stagnation: Not in your life”, VoxEU, Agosto.
OIT, (2020). “Covid-19 y el mundo del trabajo: repercusiones y respuestas”, 18 de marzo de 2020
OIT, (2020). World employment and social outlook – Trends 2020.
OIT, (2020). Young workers will be hit hard by COVID-19’s economic fallout.
Salazar, O. C. (2011). La precarización laboral y el desempleo como consecuencias del neoliberalismo y la globalización. Revista Tendencias & Retos, (16), 43-57.
Salinas, J., (2001). “TIC: ocupación y formación ¿globalización-desempleo?”. Artículo presentado en CIFO III Congreso de Formación Profesional ocupacional. Formación, trabajo y certificación, realizado del 20 al 23 junio del 2001.
Tirole, J., (2017). La economía del bien común, Taurus.
Webb, B. T Webb, S. (1909). The break-up of the poor laws, Londres, Fabian Society, 1909.
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Agriculture is the major contributor to the national economy, livelihood and employment since long. However, despite the priority in the national policies, the growth of the agriculture sector is merely around 3% that is not able to contend increasing population growth.
I would love to know- What are the challenges and problems?
Can agriculture still lead the national economy?
Why many national policies and agricultural policies could not help farmers and the agriculture sector?
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As per the agricultural sector concern not only the Nepal but all the other economies around the globe feel slowdown which may be related to pandemic outbreak coupled with other regional factors. but if we look into deep all the countries where agriculture is a major contributor seems poor and less developed compared to one those depend on service or industrial sector. The main reason agriculture is monsoon dependent, fluctuation in market price and consumer preferences severely also paly major role which are hard to manage.
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I have four independent variables that are advance to deposit, return on capital employed, EPS, dividend yield ratios, one dependent variable return on equity, and three moderating variables GDP growth, Unemployment, and Inflation . which model should I chose please guide me
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can you update us the type of data you are using so we can help you with concrete answer. This depends:
1. If your data is Panel : check for fixed and random effect models. Robustness using IV should be done
2. If your data is time series: proceed with cointegration, ARDL, NARDL models
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it is well established that unemployment affects poverty, but dose the opposite occurs ??
I need research papers about this correlation
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Thank you very much Nesrine Refaat for the interesting question.
I take the liberty of adding a few notions linked to this relationship.
Among the authors who disagree with the self-regulation of markets, there is a consensus on the deterioration in the labour market, associated with policies of structural transformation - asymmetries between the economic and the social, flexibility in labour relations, the level of the minimum wage in collective bargaining, training and employment insurance, etc. These resulted in an increase in unemployment, underemployment, overemployment and precarious employment. Workers expelled from the formal labour market face the loss of social protection and job stability through informal labour activities - as survival strategies. They also suffer a sharp fall in real wages and living conditions, and are largely below the poverty line. Thus informal subsistence employment has taken root in poor households as the only viable alternative - at least temporarily - to survive or escape poverty.
The identification of lack of availability of decent wage jobs for all who want them implies interpreting the phenomenon of poverty - whether quantified as monetary, extreme or multi-functional poverty - as being caused by systemic factors, not by individual deficiencies. In this way, unemployment can be seen as the engine of poverty and inequality, which are presented as proportionally related - since the mid-1970s in the developing countries, the poverty and unemployment rates have evolved in the same way. This is in line with Dhani Shanker Chaubey 's statement.
Although poverty is more common among people from families with little education or financial problems in their teens, 13.5 per cent of those who have never experienced financial difficulties in their adolescence are poor today - according to ILO estimates in 2013.
Neoclassical thinking refers to this phenomenon as a poverty trap. Based on the Myrdal concept of cumulative circular causation, econometric models are often used to calculate the probability of falling into poverty, and it is concluded that the persistence of poverty is strongly associated with unemployment. In this way, labour market failure is measured not only in terms of existing open unemployment rates. In addition, the increase in the level of discouraged workers is highlighted.
Unemployment is one of the manifestations of exclusion, in this case of employment, but it is not the only relevant dimension in which the concept has been used. In fact, social inclusion is the combination of what have generally been considered the three basic pillars of social integration in the Welfare State period: housing, family and work. Exclusion, as a dynamic, multi-dimensional and multi-causal process, which transforms, coexists and feeds back into the transformations of society, is a process and not a static situation, which is expressed in the field of work - unemployment, lack of income -, housing, health, residential segregation, etc.
In order to extend the discussion on some approaches used in public policies, referred to the concepts and measurements of poverty, exclusion and social vulnerability, I copy the link of an article associated to the topic: http://www.redaepa.org.ar/jornadas/viii/AEPA/B10/Busso,%20Gustavo.pdf -among the multiple existing bibliography regarding the development and debate of these concepts-
We look forward to further contributions. Greetings and available for anything you may wish to contribute.
Fernando (From Argentina)
Muchas gracias Nesrine por la interesante pregunta.
Me tomo el atrevimiento de sumar algunas nociones vinculadas a esta relación.
Entre los autores que descreen de la autorregulación de los mercados, se destaca el consenso en el deterioro registrado en el mercado de trabajo, asociado a políticas de transformación estructural – asimetrías entre lo económico y lo social, flexibilidad de las relaciones laborales, nivel del salario mínimo en las negociaciones colectivas, seguro de capacitación y empleo, etc.–. Estas tuvieron como saldo un incremento del desempleo, el subempleo, el sobreempleo y los empleos precarios. Los trabajadores expulsados del mercado de trabajo formal, enfrentan la perdida de protección social y estabilidad laboral, mediante la realización de actividades laborales informales –como estrategias de supervivencia–. Sufriendo además una fuerte caída de las remuneraciones reales y de sus condiciones de vida, pasando en gran medida a encontrarse en niveles por debajo de la línea de pobreza. Así el empleo informal de subsistencia ha tomado ascendencia en los hogares pobres como única alternativa viable – al menos transitoriamente–, para sobrevivir o salir de la pobreza.
El señalamiento de falta de disponibilidad de empleos con salario digno para todos los que lo deseen, conlleva interpretar el fenómeno de la pobreza –sea está cuantificada como pobreza monetaria, extrema o multifuncional–, como causada por factores sistémicos, no por deficiencias individuales. De esta manera, el desempleo se puede considerar el motor de la pobreza y desigualdad, presentados proporcionalmente relacionados –desde mediados de los setenta en los países en vías de desarrollo, el índice de la pobreza y la de tasa desempleo evolucionan de la misma manera–. Lo mencionado se encuentra en línea con la afirmación de Dhani.
Aunque la pobreza es más frecuente en las personas con familias de escasa formación o con problemas económicos en su adolescencia, no obstante, el 13,5% de quienes nunca han padecido dificultades económicas en su adolescencia hoy son pobres –según estimación de la OIT en 2013–.
Desde el pensamiento neoclásico se hace referencia a este fenómeno como trampa de pobreza. A partir del concepto de Myrdal de causación circular acumulativa, se suele incorporar modelos econométricos para calcular las probabilidades de caer en la pobreza, y se concluye que las persistencias de la pobreza están asociadas fuertemente al desempleo. De esta manera el fracaso del mercado de trabajo se mide no sólo en función de las tasas de paro abierto existentes. Además, se destacan, el incremento del nivel de trabajadores desanimados.
El desempleo es una de las manifestaciones de la exclusión, en este caso del empleo, pero no es la única dimensión relevante en la que se ha utilizado el concepto. De hecho, la inclusión social es la combinación de lo que generalmente se ha considerado como los tres pilares básicos de la integración social en el período del Estado Benefactor: vivienda, familia y trabajo. La exclusión, como un proceso dinámico, multidimensional y multicausal, que se va transformando, coexiste y se retroalimenta con las transformaciones de la sociedad, es un proceso y no una situación estática, que se expresa en el ámbito laboral –desempleo, ausencia de ingresos–, en la vivienda, la salud, la segregación residencial, etc.
Para ampliar la discusión sobre algunos enfoques utilizados en políticas públicas, referidos a los conceptos y mediciones de pobreza, exclusión y vulnerabilidad social, copio el link de un artículo asociado al tema: http://www.redaepa.org.ar/jornadas/viii/AEPA/B10/Busso,%20Gustavo.pdf –entre la múltiple bibliografía existente respecto al desarrollo y debate de estos conceptos–
Quedamos a espera de otros aportes. Saludos y a disposición en lo que consideres que pueda colaborar.
Fernando (Desde Argentina)
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Hi everyone,
I am trying to assess the chance for an individual to fall into the unemployment using LFS micro-data. The issue of selection bias emerged when restricting the sample to only individuals in the labour force (employed/unemployed). After consulting the literature, I found that even those who are out of labour force have to be included in the analysis to avoid the selection bias issue as suggested by (Heckman, 1979). Therefore, the model that I am thinking of doing is as the following:
•LFP= X1i β1+ E1i (1) first stage
•UN= X2i β2+ E2i (2) second stage
•Where LFP is the probability for individual i to enter the labour force, UN is the probability for individual i to fall into the unemployment, Xi represent the exogenous variables (demographic and socio-economic factors), β1,2 are parameters to be estimated, and the Ei1, Ei2 are the error terms.
Now, the questions are:
1- Do I have to have an instrumental variable? If so, could you please suggest me one. (I read that it should not be correlated to the unemployment probability in any way. In other words, Should affect the participation in the labour market, statistically correlated, but does not affect the unemployment, statistically uncorrelated.)
2- How does the inclusion and exclusion work. I have come across some papers that research include and exclude variables (not sure if in the main model or the probit and i do not know why).
Any suggestion or answer to the questions is greatly appreciated.
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There is a LM test that indicates you if the rho is sgniciantly different from zero or not (see the attachment, please).
The sign of the rho indicates the direction of the correlation between the error terms in both equations. If that sign makes sense, it will depend on the problem. Assuming that something like ability can be in the error, it makes sense that participation in the labour market is positively correlation with ability a unemployment is negatively correlation, so it could make sense.
If you do not use an exclusion restriction, referees are very likely to question the value of the analysis, unless it is just a robustness check.
I guess that one could argue that something like housing tenure should correlated with unemployment but not participation, but I cannot imagine one in the opposite sense: I would just survey the applications in order to see which variables they use.
Best,
José-Ignacio Antón
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Hi everyone!
I´m writing my bachelors thesis and originally wanted to study the effect of tuition fees on socioeconomic/intergenerational mobility. I couldn´t find any suitable theory so I´ll have to figure out a new subject.
I´v now thought about the following themes and would be extremely thankful for recommendations on theory or another interesting subject/viewpoint.
  • The effect of an additional year of schooling on intergenerational mobility; the relations theory and actualization during years 19XX-20XX. (I`ve found a dataset for mobility and would like to use STATA or R for the empirical chapters)
  • The effect of compulsory secondary/upper secondary education on intergenerational mobility
  • Interrupted work careers and subsequent earnings; gender earnings gap
  • The obligations/binding nature of unemployment benefits and its effect on the employment rate( comparing Finland, Switzerland, Sweden, USA, Denmark. Obligations on a scale from 1-5)
I`ve studied each subject, but am most familiar with economics of education and social/socioeconomic/intergenerational -mobility.
Stay safe!
Br,
Koskelo Sara
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Thank you for your question. Not finding a "suitable theory" doesn't mean that you have to change your topic. Just start with the empirical part and then figure out the theory on the fly. For a Bachelor thesis this should suffice.
Good luck!
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Trying to see how increasing minimum wage affects unemployment rates at the county level. Will look at state with federal min wage vs state with higher min wage. What variables need to be controlled for? Is there a better model/regression/method?
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In terms of control variables, you have to look at " asymmetric information theory", and for DID, it is a good method but you check the robustness with PSM-DID, Two-Step System GMM, even DDD.
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Qué estrategias recomiendan a los gobiernos locales para contrarestar la crisis del desempleo generada por el coronavirus COVID-19 en los países de América Latina?
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Buenos días Doctor.
Difícil su pregunta, pero muy interesante y le daré algunas ideas que tal vez pueden resultarle útiles. Me parece que lo primero que exige esta situación es que el gobierno se involucre directamente en la gestión de la crisis, no es momento de dejar a su suerte a millones de personas que en América latina viven de la economía informal, conozco países donde las personas viven el día a día y no pueden dejar de salir a las calles a buscarse el sustento de su familia. Hay que buscar la forma de subsidiar un tipo de economía de crisis que facilite la recuperación para luego regresar a las condiciones de normalidad, bueno de nueva normalidad.
En segundo lugar; creo que es urgente que en la economía se involucre más a la ciencia, ello garantizaría que las producciones de miles de empresas estén basadas en los adelantos de la ciencia y la tecnología lo que les conferiría mayor valor agregado. Y en este sentido, me parece urgente pasar a una economía del conocimiento en aquellos países donde sea posible. Si algo ha enseñado la crisis asociada a la enfermedad del COVID-19 es la necesidad de utilizar más las herramientas de la informática en función de la economía, eso garantizará que las personas no tengan necesidad de aglomerarse para trabajar y hará que los países exploren mercados más competitivos.
En tercer lugar; me parece imprescindible recuperar las producciones locales, ir más hacia el desarrollo de los territorios algo casi perdido en América latina. Pude ver en Perú, Brasil y Colombia que en los pueblos ancestrales atesoran una sabiduría única que puede generar productos únicos que pueden aportar recursos financieros importantes para las comunidades locales. Un ejemplo: ¿cuántos le puede aportar a las comunidades ancestrales del Perú la comercialización de la sangre de drago? Obviamente mucho, sin embargo, no son esas comunidades quienes comercializan ese producto.
Finalmente, creo que los estados tienen que imponer a las grandes empresas la obligatoriedad de contribuir al desarrollo local. No es posible que se lleven las riquezas de los territorios, desvíen el cauce de los ríos o los represen, dejen miles de hectáreas improductivas sin garantizar actividades alternativas para las futuras generaciones.
Son algunas ideas, podemos intercambiar cuando lo desee.
Saludos cordiales.
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Education and Unemployment Levels Before and After the Great Recession
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I suggest going to Eurostat:
You should select "LFS series-detailed quarterly survey results (from 1998 onwards)" -> "Total unemployment-LFS series" -> " Unemployment rates by sex, age and educational attainment level (%) (lfsq_urgaed)"
You can obtain almost any data from the EU.
Tou can also go to https://stats.oecd.org/ -> Education and training -> Education at a glance -> Educational attainment and labour-force status,
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During recent decades, huge funds have been spent on research and scientific publication. Despite this, the world still faces many complex challenges and problems, such as climate changes, water scarcity, food insecurity, unemployment, poverty, infectious and chronic diseases. So, in your opinion, what changes in trends and practices of scientific research are needed to maximize the role of research in resolving real-world problems?
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The real issue is our intent. When we conduct research because we are forced to do it then it stands no chance to come up with a solution to our real world problem. Scientists appear to be tools in the hands of decision making who make them come up with a narrative they find fit to support their cause.
The problem is not with the scientific method, it is with the practitioners.
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It seems that at the present level of science and mathematics science, we are able to measure with considerable precision the uncertainty of the shaping of many socio-economic phenomena, let us say regularly researched (measured quantitatively) in the past and now.
I conduct research on the dependence of uncertainty in running a business and the risk of bankruptcy of enterprises with the use of multidimensional discriminatory models and uncertainty indicators in 1990-2004 (the period of Poland's systemic transformation) for the scientific conference for the 100th anniversary of the Department of Economic History at the University of Poznań (planned for 2021.) .
In the science of cliometry, we adopted (Dr. D.A. Zalewski (1994); Dr. J. Wallusch (2009)) as a measure of long-term uncertainty, the variance, i.e. the arithmetic mean index of the squared deviations (differences) of individual feature values from the mean, but not literally the variance of a single variable, but a change in process variance that arises under the influence of changes in the size of the random component, i.e. there is a variable variance in the time series. Cliometrics decided that uncertainty is a derivative of variability, and this is precisely measured by variance. For a specific study, we accept long series of at least several dozen observations and calculate them in the GARCH / ARCH model. Thus, in cliometry, we consider that both uncertainty and risk are quantifiable provided we have data series.
In My Approach, I propose to use as a measure of uncertainty the ex post measurement of the number of erroneous forecasts and expectations of changes in a given indicator (scientific approach from Ferderer, J. Peter (1993): The impact of uncertainty on aggregate investment spending: an empirical analysis. Journal of Money, Credit and Banking, 25, 30–48.), e.g. GDP growth or inflation, investment, unemployment rate in relation to forecasts and expectations published in the media by a specific and selected group of professional centers dealing with a given process , a socio-economic phenomenon.
The more erroneous forecasts I detect by making an accuracy analysis (matching the old forecasts to the statistical data disclosed by a research center that regularly analyzes a given phenomenon), the higher the economic uncertainty index is calculated for a given phenomenon. My approach derives directly from the technical problem of uncertainty of measurement with a physical instrument explained by physicists.
The problem of uncertainty in running a business
For example, how do I assess the uncertainty in running a business (company) in a given country and time, e.g. 12 months. Well, I compare the variability (variability index) in two series of data (observations): the first series is the statistics of newly opened businesses, and the second series is the statistics of businesses closed and suspended in the same time (12 month). In my opinion, the imposition of the variability in these two series of observations gives a very good understanding of the scale of uncertainty in economic activity in a given year or years in a given country.
In my opinion, uncertainty is like a shadow changing its form with each change in the incidence of light rays, the more I can notice the more the light source and the object on which the light falls.
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The analogy of light source and shadow is a good one ! The higher the risk, the higher uncertainty?
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What do you think about implementing Industry 4.0 model in developing country? As we know, many developing country have high unemployment rate, and Industry 4.0 usually involve automation that reduce workforce needed in an industry
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In my opinion there is no 'best practice' in transferring technology Taras Danko . Each country will be very different with the another because the root cause of need of a particular technology is different. But in my opinion, one thing is sure, the main actor for this transfer are producer of manufacturing equipment/technology. This because developing country do not have solid scientific foundation, so the only one thing they (developing country) can negotiate is adjusting the new technology (industry 4.0) to particular case in that country
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Latin America is the current epicenter for COVID-19 with more than two million cases and Brazil has already lost its total control with collapsed economy.
At least 7.8 million Brazilians lost work between March and May, according to new figures released by the country’s statistical agency on June 30, 2020.
June 30, CNN
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Dear Muhammed Ashraful Alam the IMF predicts that the world will enter into a recession worst than the Great Depression of 1930, with a preliminary estimation of the economic impact of the crisis at US$ 2 trillion. The International Labour Organization (ILO) estimates that approximately 25 million people could be unemployed and those in informal activities would suffer most from the absence of social protection.
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My research is on the relationship between unemployment and stress and well-being, and how gender differences moderate that relationship.
I'm quite new to research, as this is for a university essay and I'm not sure which validated scales to use. I came across the 'Perceived Stress Scale' but I wasn't entirely confident in whether it is useful to use.
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There are a number of measures, and I have used the Perceived Stress Scale. Before choosing a scale, you should probably do a full literature review of the strengths & weaknesses of each scale, as well as think about exactly you are thinking of when you are interested in stress, e.g., daily hassles, presence of stressors, reactions to stressors.
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Dear Colleagues,
many challenges ahead of us. The pandemic crisis and its repercussions on employment, the coming climate and ecological apocalypse, the aging population (especially in some areas of the globe). Despite a minority that calls for a radical switch in our way of production, lifestyle and consumption, a large part of the practictioners and researchers believe that these challenges can be faced trhough technological innovation with the hope that somehow, at some point, we'll find solutions withouth compromising how we live today. In between those two fronts, many shades of grey and halfway solutions. Research in all the cases mentioned, is rich and encompasses a broad range of alternatives allowing one to position and build knowledge in the community that more represent his ideals. In all the cases though when it comes to working hours reduction, just few dozens of results pop up. It is impressive , how in the last 40 years management research hasn't focused at all on investigating the possibility of reducing the working hours maintaining a costant pay, seen the increase in annual productivity. Some of the reasons are quite obvious if we look through the lenses of ortodox approaches: increased complexity, power relations, neoliberalism-managerialism etc (I know, this is very superficial and oversimplified but it is just to make sure future respondents to this question won't focus on the things I already know). My question instead would be: why critical management scholars, eterodox economists, did not produce enough and relevant research on the topic except for a few books? To me, with just a spoiled impression on the topic, this could represent a solution to many ecological problems, unemployment, extremy poverty, depression ecc ecc. The pandemic brought back this topic to the spotlight and I would like to write something on that. Maybe trhough an experimental design (I am just at the beginning of the process, this idea is still in Plato's Iperuranio). Would you like to discuss the topic with me? Any idea, research article?
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Dear Giacomo.
I share its worry, but I am far from being provided with knowledge experimenting. I believe that this sanitary - economic crisis, as well as the previous ones, bring old questions inherited from classic authors that were never decisive. As its consultation: because changes are not realized on the labor market to reduce the maximum time of the labor day although some countries have advanced more than others in this topic – and to allow so that they deposit major workpeople quantity, obtaining a fall in the unemployment, as well as also to increase the social welfare level?
The times seem to accompany this claim, we see that the young people at educational level very superior to its parents, obtains every time less sure and stable work places, differing between them for the more and more concentrated familiar patrimony. Also the increase in the unemployment valuations between the adults with higher education – with regard to the adults without top average education, according to the report Panorama of the Education 2014 of the OECD –. Every time they are major the documents quantity with estimations with regard to the quantity of million clear work places that will get lost to future, and than the emergence of the new works.
Dear Giacomo, thousand pardons for moving away from its question.
Leaving aside the golden epoch of the capitalism – strong relation between the wages and the productivity – in the period 1980-1999 the world GDP increased in 71,7 %, and between the year 2000 and 2019 in 70,0 % – in constant dollars of 2010, according to the base of the world Bank, https://datos.bancomundial.org/indicator/NY.GDP.MKTP.KD) –. It would be a slightly significant difference to be the main explanation of the fall of the participation of the wages in the added value – the mentioned can be thought superficial, since there is not clear as quantifying the contribution that they do in the real productive process, if the last one is valued finally at stock-exchange level according to multiple types of investors –. It might advance under the assumption, of an increase of the financial revenue in the total participation of the profit. In case of accepting this conjecture, the concentration in the personal distribution of the revenue is every time major – less persons concentrate more quantity of financial wealth –. I believe that the important thing would be to have quality statistics, for explicitar this. Pardon for not being able to bring any answer, but, show on the contrary over doubts. In this context of generation of information in real-time in any point of the planet: would it be easier to give answers of social utility in our more and more complex and changeable societies?
Estimado Giacomo.
Comparto su inquietud, pero estoy lejos de contar con conocimiento experimentando. Creo que esta crisis sanitaria-económica, así como las anteriores, traen viejas preguntas heredadas de autores clásicos que nunca fueron resueltas. Como su consulta: porque no se realizan cambios en el mercado laboral para reducir el tiempo máximo de la jornada laboral–si bien algunos países han avanzado más que otros en este tema–, y permitir para que ingresen mayor cantidad de trabajadores, consiguiendo una baja en el desempleo, así como también aumentar el nivel de bienestar social?
Los tiempos parecen acompañar este reclamo, vemos que los jóvenes con nivel educativo muy superior a sus padres, consiguen cada vez empleos menos seguros y estables, diferenciándose entre ellos por el patrimonio familiar cada vez más concentrado. También el aumento en las tasas de desempleo entre los adultos con educación superior – respecto a los adultos sin educación media superior, según el reporte Panorama de la Educación 2014 de la OCDE–. Cada vez son mayores la cantidad de documentos con estimaciones respecto a la cantidad de millones de empleos netos que se perderán a futuro, y al surgimiento de los nuevos trabajos.
Estimado Giacomo, mil perdones por alejarme de su pregunta.
Dejando de lado la época de oro del capitalismo – fuerte relación entre los salarios y la productividad–, en el periodo 1980-1999 el PIB mundial aumento en 71,7%, y entre los años 2000 y 2019 en 70,0% –en dólares constantes del 2010, según la base del Banco mundial, https://datos.bancomundial.org/indicator/NY.GDP.MKTP.KD)–. Sería una diferencia poco significativa para ser la explicación principal de la caída de la participación de los salarios en el valor agregado –lo mencionado puede considerarse superficial, dado que no es claro como cuantificar el aporte que hacen en el proceso productivo real, si este último es finalmente valorizado a nivel bursátil según múltiples tipos de inversionistas–. Se podría avanzar bajo el supuesto, de un aumento del ingreso financiero en la participación total de las ganancias. En caso de aceptar esa conjetura, la concentración en la distribución personal del ingreso es cada vez mayor –menos personas concentran más cantidad de riqueza financiera–. Creo que lo importante sería disponer de estadística de calidad, para explicitar esto. Perdón por no poder acercar ninguna respuesta, sino por el contrario, manifestar dudas. En este contexto de generación de información en tiempo real en cualquier punto del planeta, ¿sería más fácil dar respuestas de utilidad social en nuestras sociedades cada vez más complejas y cambiantes?
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What is the impact of the agenda 2030 on female unemployment reduction?
The world is engaged in gender equality via the agenda 2030 on Sustainable Development Goals, since 2015. There is supporting literature indicating female discrimination in work place including accessing to employment for female. The goal 5 of the Agenda 2030 predicts achieving gender equality, and empowers all women and girls. Additionally, the goal 8 indicates promoting sustained inclusive, and sustainable economic growth, full and productive employment and decent work for all. However, the effect of the implementation of the Agenda regarding female unemployment reduction is not known. To bridge the gap f knowledge, an assessment was made to investigate whether there is significant change in reducing female unemployment in countries whose GNI for 2019 is under $ 4000. 43 countries were then analyzed using paired sample t test. The result indicates that there is statistically significant reduction of female unemployment in 2019 (median = 4.74, sd= 6.02) compared to 2015 (median =4.92, sd = 6.34), w=690.50, p<0,001.
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... Evidence from five European countries...This study explores the relationship between both individual and aggregate unemployment and union dissolution risk in five European countries before the recent economic crisis. Using rich longitudinal data from Belgium, Finland, France, Germany, and Italy, the empirical analysis, based on discrete-time event history models, shows that male unemployment consistently increases the risk of union dissolution. While a strong association is observed between male unemployment and separation at the micro level, no association is found between male unemployment and union dissolution at the macro level. The results for female unemployment are mixed, and the size of the impact of female unemployment is smaller in magnitude than that of male unemployment. In Germany and Italy, where until very recently work is less compatible with family life than in other countries, female unemployment is not significantly associated with union dissolution. ... Solaz, A., Jalovaara, M., Kreyenfeld, M., Meggiolaro, S., Mortelmans, D., & Pasteels, I. (2020). Unemployment and separation: Evidence from five European countries. Journal of Family Research, 32(1), 145-176.
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Hello everyone!
I would like to ask if someone of you knows of any unemployment-related scales (psychological consequences and effects of unemployment), preferrably in german language?
Are there any scales concerned with some of the psychological correlates of unemployment?
Thanks a lot already.
Best regards,
Helena
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Et= Employment; Nt=Population; L.F.P.Rt= Labor Force Participation Rate
  • We use the first difference of equation (2) to calculate changes in employment, which we do over two broad periods: 1990–2010 and 2010–2030.
  • Equation (2) suggests that changes in employment over time are due to changes in any of three sets of variables—population, labor force participation rates, or unemployment rates—and thereby offers a framework for decomposing past and future projections of employment.
  • For example, by holding unemployment rates and labor force participation rates constant at their time t values, we can observe the change in employment at time t+1 that is attributable to changes in the population size. Doing so allows us to identify the primary demographic drivers behind historical employment changes and provides insight into the nature of future employment needs.
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Thank you so much for responding. This equation is copied from
following paper:
https://www.nber.org/papers/w24835.pdf and they have multiplied 1-ur with population and LFPR.
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The classic post-war, V-shaped recession occurred in 1957-58. Its peak to trough annualized quarterly decline in real GDP -3.6%, compared to -4.0% for the Great Recession 2007-09. In contrast peak to trough decline during 1973-75 was -3.1% and 1981-82 -2.6%. A key reason why the contraction of 1957-58 is not remembered among the most costly is that after the quarter containing the NBER trough month (April), real GDP grew at an astonishing average of 9.1% in the next four quarters. So the actual real GDP path returned to potential GDP so quickly that a large loss in out was prevented. This helps explain why the unemployment rate peaked at 7.5% in 1958. During the 1973-75, 1981-2 and 2007-09 unemployment peaked at between 9 and 10.8% However during the last three recessions, which ranged from mild to severe, output was notoriously slow in returning to potential. So what will happen in 2020-2021? Will there be a sharp rebound after a horrific trough in the 2nd or 3rd quarter, or will the return to potential be agonizingly slow? Will the "Great Recession "be followed by a V-shaped contraction that is a deeper version of 1957-58 but with a sharp rebound or a longer-lingering Little Depression?
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Paul: I think the economic recovery will be extremely slow following the current Recession in 2020. I say this because of the COVID-19 pandemic, which will require a vaccine and/or cure before the economy can fully open up.
Many economies are shut down right now due to the COVID-19 spread. Government officials are hesitant to open the economy back up because it could cause the virus to spread more.
Most experts say a vaccine won't be available until Spring 2021, at the earliest. Even if this occurs, it will take time for a vaccine to be produced and distributed to so many people in the world.
Additionally, as the economy is shut down and some companies go bankrupt or close, the number of unemployed people is going to increase significantly. This will greatly reduce household spending, which will slow down the economic recovery even more. It will turn into a vicious circle: Economy shut down, sales down, laid off workers, less household spending, repeat, repeat, repeat, etc.
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There are many debates on the impact of foreign direct investment inflows on gross domestic product in host country. However, little is known about the indirect effects of foreign direct investment inflows on gross domestic product. The result of the analysis confirms the existence of direct effect ignoring how the effected was generated through some other variables.This may be due to the methods that are generally used in the research while analyzing the relationship between foreign direct investment inflows and gross domestic product. Some of the methods used are multiple regression models (Abbas, Akbar, Nasir, Aman & Naseem, 2011), correlation and regression model (Nadeem, Naveed, Zeeshan & Sonia, 2013), cointegration analysis (Nosheen 2013), simple regression (Tamilselvan, & Manikandan, 2015), generalized least squares estimator (Khan, Shiraz, Mehboob & Farhan 2014). They concluded on the positive effect of foreign direct investment inflows on gross domestic product without considering the possible indirect effect.Not analyzing the existence of indirect effect that foreign direct investment may have on gross domestic product through a third variable may lead to a biased conclusion. One variable may have effect on the other variable trough a third variable, without this there may be no direct effect.
By applying causal steps procedures recommended by Baron and Kenny (1986), I analyzed the relationship between foreign direct investment inflows (FDI) and gross domestic product (GDP) in low and low middle income countries. The result of the analysis shows that there is a complete mediation of FDI through house hold consumption, a partial mediation of FDI through female labor participation, a partial mediation of FDI through dependency age youth, and partial mediation of FDI through female unemployment rate.
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Dear Mr. Goran, thanks you for your new ideas.Exploring indirect effect of FDI on GDP through the job creation and trade is what I m doing now in my dissertation. I m working on Sub- Sahara Afrian countries, and the result are in line with your comment. There a partial mediation Partial mediation for female unemployment rate,exports, imports, female employment in industry, and services.
Best
Antoine
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AI and automation may reduce manufacturing costs but also may increase unemployment. What other benefits/opportunities and negative effects could Automation and Artificial Intelligence may have on the economy?
Thanks!
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Nothing in my view, It is very hard to interpret the new situation as a disruption. Seems better if we consider it as a transformation. Unlike many, I believe it does not necessarily lead to disruption. Some vocations may be diminishing, while others come into existence.
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Has the relocation of large factories from highly developed countries to countries with cheaper labor costs caused unfavorable situations of rising unemployment in some regions in your countries?
It turned out that from the global financial crisis of 2008, those countries in which the domestic industry was more developed faster.
Some industries, including large factories, have been expatriated to countries with cheaper labor costs.
For a corporation that decides to move such assembly plants, it is a business goal of saving labor costs.
However, in the city from which this factory emigrated, unemployment is rising. If it was a small town and the factory was the main employer, the problem of a significant increase in unemployment on the local market arose.
In some countries, restrictions have been introduced to limit the scale of this process of emigration of large production factories and sometimes entire branches of the economy to other countries.
How do you feel? Should the governments of individual countries regulate these issues, should liberalization be in this matter or should it be under the control of the state, i.e. the government of a given country?
Please, answer, comments. I invite you to the discussion.
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True. Textiles has moved from India to Bangladesh & Vietnam.
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I am looking for initial studies revealing arguments which prove relations between number of infected people, lockdowns and unemployment rate.
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In this study, it is mentioned, among other data, the number of people which suffer to lose their jobs (Hospitality Industry)due to the coronavirus:
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I am trying extract the NSSO data (employment and unemployment) and am completely clueless about the weights that are given.
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The use of multipliers/combined weights are for representation of the whole population parameter in a NSSO survey.
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Contrairement aux résultats de beaucoup de chercheurs qui ont trouvé une relation directe entre les investissements directs étrangers et le produit intérieur brut; les résultats de l'analyse de la cointégration ne trouvent aucune relation directe entre les investissements directs étrangers et le produit intérieur brut.Ce sont les effets induits par les investissements directs étrangers qui impactent le produit intérieur brut.
The analysis shows that GDP and FDI are auto collated to the previous values. The analysis also confirms that there is no long term relationship between GDP and FDI. As consequent, foreign direct investment does not affect, directly, gross domestic product. The consequence of FDI can have positive impact on GDP (reduction of unemployment, increase in production of goods and services, increase in tax collected, increase in investment,increase in exportation, etc). The result shows that investors do not consider GDP only while analyzing market because regions with high GDP did not get highest FDI.
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Yes, FDI has a direct impact on GDP. The GDP calculation has an investment component which includes amongst others, fixed investment which is factories. When foreigners set up factories and install machineries it will be included here. There are indirect effects like employment and use of transportation, utilities and land purchases. So, FDI has a big impact on some countries GDP where there is no domestic investments.
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Hi,
I wish to calculate the weighted average of the following employment related indicators in NSSO dataset at district level:
  1. Labour force participation rate (LFPR)
  2. Worker Population Ratio (WPR)
  3. Proportion unemployed (PU)
  4. Unemployment rate (UR) Can someone please guide me on the correct approach of constructing these indicators (I am not able to understand how to use weights)?
Definition
(1)Labour force participation rate (LFPR)
{(no of employed persons +no of unemployed persons)/total population} *100
(2)Worker Population Ratio (WPR)
(no of employed persons/total population) *100
(3)Proportion unemployed (PU)
(no of unemployed persons/total population) *100
(4)Unemployment rate (UR)
{no of unemployed persons/ (no of employed persons +no of unemployed persons)}*100
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Please see codes (written in stata) below. I have written the codes for rural region (so only considered visit1).
The variables name would change, but i hope it would give some direction
** Do file for LFPR, WPR, UR
svyset status_code_ps [pweight= mult]
gen employment_status_ps =0
replace employment_status_ps =1 if status_code_ps<=51
gen employment_status_ss =0
replace employment_status_ss =1 if status_code_ss<=51
gen employment_status = 0
replace employment_status =1 if employment_status_ss ==1 | employment_status_ps ==1
svy: proportion employment_status
///employment status is WPR
svy: proportion employment_status, over( sector)
gen unemployment_ps =0
replace unemployment_ps =1 if status_code_ps==81
gen unemployment_ss =0
replace unemployment_ss =1 if status_code_ss==81
gen unemployment =0
replace unemployment =1 if unemployment_ps ==1 | unemployment_ss ==1
*** LFPR calculation
gen lfpr = 0
replace lfpr =1 if employment_status ==1 | unemployment ==1
svy: proportion lfpr, over( sector)
*** unemployment rate (this is not matching) need to check it out
svy: ratio unemployment/lfpr, over( sector)
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The data that I am looking for are for my master thesis, where I am interested in the effect of culture on preferences for redistribution. My main data source is the European Social Survey (ESS), hence countries in my sample are mostly European. I have already explored the databases of the World Bank, Eurostat, OECD and other cross-national ones, but the series I am interested in either come with many missing observations or in most of the cases they start quite late.
If you have encountered something similar as researchers in the past or if you simply know any databases with long historical data on income inequality or unemployment rates, your recommendations will be much appreciated!
Thank you very much in advance!
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Pak @Yuri Mansury. Im interesting with your suggestion. It's also provided for Indonesia case? I would like to measure impact of institution on income inequality.
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Much has been discussed about the policy that best contributes to the incorporation into the labor market of young workers. In this discussion, I liked to focus the question on three points of view, higher education, vocational or professional training or the promotion by the governments of entrepreneurship and self-employment of young people. Regarding university education, during the last half century it has been seen as a tool for social mobility. However, many countries with high rates of university graduates have high levels of youth unemployment and important percentages of graduates work below their qualifications, while inequalities in the labor market grow. I thank you in advance for your opinions.
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The best plan is a plan (policy) that provides more options. Training in the broadest sense of the word, seems to be the best policy for youths. But training needs to be "credentialized" by a trust-worthy party. Better still if it's the crowd that does this instead of a invested-interest party. So "proof of work" has trumped "proof of stake" in education. Can-do is often what gets youth employed, not willingness to do. Because the later does not address the short term performance requirements of businesses
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There are four primary issues concerning the employment of graduates in Malaysia. The issue of rising unemployment among graduates; a mismatch between the abilities of graduates and the necessities of employment; the suitable of graduate job and the shrinkage of job in public and private sector. Therefore, researchers looks at the youth entrepreneurship development in Malaysia which to examines and identifies the entrepreneurial characteristics and skills for transformation and improvement in the delivery of entrepreneurship
programs.
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I have to analyze a regression and estimate how the crime rate responds to changes in the state unemployment rate (unemp in the Stata output). The outcome variable is lcrimepc, the logarithm of the total number of crimes per capita in a specific city. The coefficient is 3.12. Given that the unemployment rate is measured in percentage points, how an increase of 1 pp affect the argument of the logarithm?
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Hi,
for interpretation, you can use the coefficient of elasticity. Elasticity is a measure of the sensitivity of one variable (for example, demand or supply) to a change in another (for example, price, income), showing how many percent the first indicator will change when the second changes by 1%. When using a logarithmic variable instead of an absolute change in one variable, we obtain its relative change.
Unfortunately in the editor there is no way to write formulas, but I think that you will succeed.