Questions related to Labor Economics
In the world of employment, labor distribution companies usually use agents to persuade and recruit people in rural areas to become domestic workers or migrant workers. If so, then the persuasion or recruiting process by the agents can be seen as "selling" process, and in the candidates point of view, the decision to accept the offer of the agents can be interpreted as "buying" or "not buying" process. Any thought?
The question is pretty self explanatory, but I am looking especially for female labor force participation, where the focus has been on rural areas? especially in Asian and African countries.
I have been tasked with creating a policy brief for my development economics course, so would really appreciate any such information on existing policy briefs or ones implemented in the past too.
At the moment, I have one explanation in mind. If labor productivity is high, firms may focus more on reinvestment prospects instead of repaying loan installments. But I cannot find any prior literature in support of this claim. I would appreciate it if you can provide any other explanations or refer to any relevant literature.
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
From the beginning of the industrial revolution and the description of the functioning of enterprises in the conditions of market structures, in the trend of classical economics, three types of production factors dominated in the production processes defined by three slogans: land, labor, capital.
However, successively with the development of industry and technological progress in the 20th century, other categories of production factors, typical for economies largely based on information, are added to these classic factors of production.
These factors of production, whose role in many industries has been growing since the 1960s include: knowledge, information, technology and innovation.
In view of the above, the current question is: In what branches of industry such production factors as knowledge, information, technology and innovation are currently or become the most important?
Please, answer, comments. I invite you to the discussion.
Many studies cover the positive relationship between women's education and participation with GDP growth. however, very few studies covered the effects of women's participation on wages, and these few studies are usually very general and do not cover specific sectors.
I remember reading many years ago (perhaps more than 40 years ago) that Antonio Gramsci wrote somewhere about the time awareness of workers who originated from Sardinia. According to my vague memory, he argued that Sardinian workers had more loose time awareness than workers who grew up in Torino and its suburbs and it reduced their labor productivity.
Does someone know where Gramsci made this kind of argument? If possible, I want to know the exact argument he made and the circumstances of this argument. It is possible that I read it someone's paper other than Gramsci himself.
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.
I was curious about the possible Machine Learning methods or approaches for outlier (anomaly) detection in labor economics.
I tried to search for this matter, but could not find any pertinent research to this problem. It would be a pleasure if anyone knows any scientific thesis, paper or survey about anomaly detection in labor economics.
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.
How could one measure changes (improvements) in conditions of employment across many countries and over periods of several years? Are there any datasets readily available? And what specific indicators one could seek (assuming increase in wages would be one such obvious indicator, what else?} And is there any literature on this topic you're familiar with?
Everyone knows intuitively that technology, especially one that can develop its "intelligence" through learning, displaces and will displace people from the labor market. How do you think what other legal or social consequences, besides losing a job, may result from this? Will it affect every country where international production takes place? Will there remain places where it will still be profitable to use the work of human hands?
Thanks in advance for any thoughts.
The technological revolution Industry 4.0 is currently one of the major determinants of the economic development of highly developed and developing countries.
Therefore, the issue of Industry 4.0 should be introduced as an additional subject in studies in the fields of management, administration, economics, IT, master of business administration, etc.
In view of the above, I am asking you: What new professions will be created on the labor market in the future due to the development of the Industry 4.0 technological revolution?
Please reply. I invite you to the discussion
I am working on wage differential between immigrants and natives and I see in the literature mostly hourly wage has been used to identify the earnings of individual I am just curious if there is any theory or intuition behind that.
Discouraged labor are economically inactive, because they are not working and they no longer look for a job, as they have given up hope!
Actually, I am about to estimate the effects of educated labor force supply (or better to say production) in higher education, on the unemployment rate. To do this in an strong way, it is necessary to start the discussion in a macro- or labor economic background and specify the relationship through a mathematical framework (e.g. similar to Jones ), However, most of the similar studies -as far as I have seen- have not provided such a background.
I would be grateful if anyone can introduce the required framework.
Traditionally, economists have approached international trade and technological change from the perspective of countries as a whole. In contrast, recent research has emphasized cities and their local labor markets as the appropriate “unit of observation” when studying these issues. This regional approach is critical to understanding the heterogeneous effects of trade on labor markets in large countries, such as the United States. In the last few decades, a select group of U.S. cities such as Boston, New York and San Francisco have become emerging centers of global comparative advantage in new knowledge-based sectors, while other formerly industrial cities, such as Cleveland and Detroit, have lost their comparative advantage in traditional manufacturing sectors and experienced broad declines.
To promote research on these issues, the National Bureau of Economic Research (NBER), with the support of the Smith Richardson Foundation, will convene a research conference in Cambridge, Massachusetts on October 25-26, 2019. The conference will be organized by Edward Glaeser (Harvard University and NBER) and Stephen Redding (Princeton University and NBER).
The conference aims to draw together researchers from labor economics, international trade, public finance, urban economics, and related fields to address a range of issues concerning cities as centers of comparative advantage and other related themes:
§ How has globalization contributed to urban decline in some cities, and urban renaissance in others? How has it affected city-level labor markets and economic activity more generally? How has technological change influenced the nature of economic activity in urban and rural areas?
§ Why can some cities, like Seattle, successfully transition from an industrial to a post-industrial economy? Are labor market differences important contributors to this variation? How have transportation and industrial technologies shaped the spatial distribution of economic activity?
§ What are the implications of heterogeneous local labor markets for wage and income inequality? To what extent has there been an increased sorting of workers by skill across cities? Why has migration from poor places, like Detroit, to rich places, like San Francisco, become so sluggish? To what degree does trade in goods and services reduce the need for labor mobility?
§ How do public policies affect the growth of urban areas? Which place-based policies improve labor market outcomes for urban workers? What are the possible responses to the decline of industrial cities and industrial heartland of the United States? What policy issues emerge from the agglomeration of economic activity in new centers of comparative advantage?
Papers are welcomed on all aspects of cities as centers of comparative advantage. Both theoretical and empirical research, and combinations, are welcome. To be considered for inclusion on the program, papers must be uploaded by Sunday, August 25, 2019, to the following site:
Submissions from authors with and without NBER affiliations are welcome and submissions from early career scholars, and from researchers from under-represented groups are especially welcome. Please do not submit papers that will be published by October 2019. Decisions about which papers will be included on the program will be announced in September, 2019.
The NBER will cover the hotel and economy class travel cost for up to two authors per paper included on the program. All co-authors are welcome to attend the conference; space permitting, other participants are also welcome. Please direct questions about this project to email@example.com.
These types of questions have appeared many times in every era of the technological and industrial revolution, the period of accelerating technological development. These types of questions have already appeared in the periods of increasing the scale of objectification, arming technical human labor, from when the processes of manufacturing goods in manufactories transformed into mass production. This was the case during the Industrial Revolution of the XIX century, when the invention of a steam engine significantly accelerated the development of industry and mass production. Then, the introduction of tape production in various branches of mass production in the early twentieth century. In the second half of the twentieth century, ie in the era of subsequent stages of mechanization, automation, then the computerization of the production of many mass goods, this question appears again. Through these periods of technological progress, national economies have been transforming structurally from agricultural, industrial to modern-day domination of services. At the same time, the importance of new generation factors, which include information, technology, entrepreneurship and innovation, was gradually growing. Some branches of industry were shrinking, others were growing in the whole production of goods in the economy. At the same time, new professions, professions and specializations of human work were created, related to information, IT, analytical and technological services related to the development of new fields of knowledge and technology. So the earlier fears about the lack of work for people in connection with the technical progress that took place over the last several hundred years turned out to be essentially exaggerated. However, currently the same questions reappear: Can the development of robotization and computerization cause a significant rise in unemployment in the future? If such questions arise, then we are dealing with another era of technical progress or another technological revolution. The attributes of this revolution are also increasingly added to the development of new online media, computerized computing techniques, artificial intelligence, machine learning, Big Data, etc. in the applications of such areas of knowledge and science as biotechnology, metrology, ecology, energy, communication, medicine and many other fields of life science and new tech. In connection with the above, please answer the question: Can the development of robotization and computerization cause a significant increase in unemployment in the future?
Please, answer, comments. I invite you to the discussion.
The theory of optimal taxation is often based on the neoclassical standard model of the labor market. That model includes the assumption that a household can choose freely how much to work and how much to enjoy leisure time. In such a framework, households derive utility from consumption c and leisure time z: u(c,z), where total time T is divided between labor l and leisure z, i.e. T = l + z. The time spent on labor is remunerated at wage w, so that households have an income y = wl that they can then consume.
In reality, however, households do not have the freedom of that continuous labor-leisure choice. It's rather the binary choice to accept a job or not. Moreover, for example, the neoclassical model predicts that a minimum wage causes unemployment. We do not observe this in reality.
Given the shortcomings of the neoclassical model of the labor market, how useful is it for a) advancing economic theory on optimal taxation and b) informing policy making? Is there a better alternative?
As an economist and secondary education economics professor interested in education and labor economics I want to understand the phenomena of skill development in both the educational system (with an special focus on secondary and higher education) and the workplace, and their interactions.
This knowledge will be useful to improve educational and job-market related policies.
does anyone have a good idea for an instrument for unemployment rates? It should be enogenous to GDP growth and crime rates. Any references to literature would also be appreciated, so far I only know of the Raphael and Winter-Ebmer paper from 2001 that use such instruments.
The Bankwest Curtin Economics Centre (BCEC) at Curtin University, together with the Economics Society of Australia’s Women in Economics Network (WEN) are pleased to announce the Australian Gender Economics Workshop.
More info: http://bit.ly/2wYNaHO
We are also delighted to confirm our keynote speakers: Professor Alison Booth (Australian National University) and Associate Professor Betsey Stevenson (University of Michigan).
While substantial progress toward gender equity has been made over the past decades, key gaps in various life aspects relating to family, education, employment, wealth, security, voice and agency remain. There is a need for new insights to better understand the role and impact of gender on all economic and social domains, and to translate these insights into actions. The workshop aims to help fill this gap.
This workshop will provide researchers with a forum for presenting and discussing innovative research incorporating gender analysis in all areas of economics. We invite both theoretical and empirical contributions to the workshop, but priority will be given to papers that can inform policy-relevant questions.
The workshop will include a special policy session involving senior influencers from government, research, industry and not-for-profit communities. The purpose of this session is to draw research insights from the workshop together in ways that will actively shape policies to enhance the status of women across the full spectrum of economic and social outcomes.
Researchers interested in participating in the workshop should submit an extended abstract or a full paper by email to Astghik Mavisakalyan (http://bcec.edu.au/about/people/astghik-mavisakalyan) by November 17, 2017. Notifications will be sent by November 24, 2017. If accepted, the authors will be required to email their full paper to Astghik Mavisakalyan by January 19, 2018.
Authors who are invited to present their papers are expected to participate in the entire two day workshop. There is no registration fee for presenters however they will be responsible for covering their travel and accommodation expenses. Practical information will be emailed in due course. Meanwhile, inquiries related to travel to the workshop and other practical matters should be addressed to Kelly Pohatu (http://bcec.edu.au/about/people/kelly-pohatu).
I am working on a project called "Diversity and Team Performance: Evidence from Indian Premier League." There might be some endogeneity in the team diversity as the players are not randomly assigned to the teams. I am sure that, the endogeneity issue here must be minimum. However, the referee will definitely ask for it when publishing. So, I am looking for a good Instrumental Variable (IV). Anyone have any idea about it?
By the way, i tried the 2009 problem of not playing Pakistan players. But the change is very small. And if it is, it might have affected 2009 and to minimum 2010 season. I am looking forward to your suggestion.
Many cities and states in the United States are pushing the Minimum wage higher and higher. Many have a goal of $15 an hour or more.
As the Minimum wage goes higher and higher, what are the negative consequences (drawbacks)?
Do you believe their is an Upper-limit to the minimum wage, where the negative effects are greater than the benefits? Why or why not?
As far as I know all countries are currently experiencing gerontogrowth, but not all countries are experiencing population aging. This is the case of Mozambique. Is there anybody investing this difference, besides obviously Gérard- François Dumond, as I acknowledge in a recente paper? see: https://authors.elsevier.com/a/1V4z3,oK5hcTAi
I have the data of NBA Players of 10 years including their age, experience, games played, assists, field goals, minutes played, salary, positions, nationality, free throws, offensive rebounds, defensive rebounds, steals, blocks, points etc.
Worker cooperatives, labor societies and self-managed enterprises are present in all democratic societies. They are generally larger and older than their capitalist twins, pay higher wages, produce stable jobs, and dismiss less during economic crises. Their employees also suffer less preventable health problems, are less stressed and live longer. However, their presence is small in both numbers and participation in GDP, although it has been increasing since the 2008 crisis. This raises the question of how to encourage the creation of new democratic enterprises?
I am designing an experiment in economics that will have subjects do a real effort task. The task will be to find pairs of identical letters in a text.
This type of task has already been used in other experiments in economics, yet I am unable to find what text is usually given to subjects - I suppose there must be a "standard text" to permit greater comparability between studies, but I can't find anything.
Do you know what material is generally used for tasks where subjects have to find pairs of identical letters in a text, please ?
GDP= Trade openness + POP+ FDI + INF+TECH(dummy) + e
I want to use the technology as a dummy variable if the technology adopted in the country then we use the value 1 otherwise 0.
Kindly help me as per your expert opinion.
I would like to do my graduate research on Rate of Return on Education. I've thought about the mincer model but I have some concerns.
1. I will survey employees online using online surveys, is it an appropriate approarch to select a random sample? (micro data needed aren't available for my country)[I'm in a Gulf country where there are no people below poverty line and about 92% of population uses internet that is even publicly avaible) Info will be spread through instant messaging and emails (asking university to send the email to staff and students who may pass it to others and other national social media accounts)
2. Due to some time limitation and in order to meet graduation deadline I can collect about 150 to 200 replies. Is it workable?
3. The variables I am thinking about are (Salary and Wages, Working Hours, Educational Level, Years of working experience, average base starting salary after high school, training program length, gender, parents education). Are they enough to conduct the research?
4. What are the programs I can use to process data for this model
5. Suggestion on applying this model or another model.
Thank you very much
Would expanding the levels of flexibility for movements of talent between firms and within firms result in a positive productivity impact (refer section 1, page 5 on Policy Document attached). On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ? Are there empirical data to support your assertion ?
Policy perspectives aimed in favour of unshackling SME’s of unnecessary strictures and empowering SME's to achieve talent-driven, outwardly-focused global competitiveness should feature flexibility to respond to market dynamism.
Flexibility covers a wide range of issues including:
a) Labour force training should be flexible in its delivery and not be rigidly tied to historical sectors and industries. Training content and packages should rather be dynamically adjustable and malleable to suit emergence of new sectors and industries. Responsive repackaging should be a key feature
b) The picking of winners and locking in / redirecting training resources to those ends is to be discouraged. The identification of areas of comparative advantage and repurposing training resources to those ends is also to be discouraged. Preference is for flexibility to be able to match market demands. Where appropriate, then time-limited Tax Incentives may be dynamically deployed to encourage training in emergent new sectors. However, there is a danger of having these incentives becoming institutionalised and remaining on the books way past their useful and value-enhancing period. Constant policy and legislative re-calibration would therefore be required.
c) Certification and training of the labour force should seek to produce an outcome where human talent is flexible and have the trained / certified individual be imbued with the capacity and capability to respond in a dynamic way to the varying job opportunities that will emerge over their lifelong working cycle.
d) Hire and Fire practices should be reviewed to eliminate rigidity and so adjusted to build in higher levels of flexibility in order to
(1) allow for easy and smooth movement of talent dynamically between firms and sectors, reducing stickiness and enhancing responsiveness as market demands change;
(2) allow for smooth movement within firms. As staff transition through their individual life cycles, job cycles and task cycles, Personal Productivity Performance changes and impacts their work output.; in some cases, upwardly and in some cases, downwardly. As individuals yearn for differing work-life balance states, then the SME firm needs an ability to flexibly treat with these employee desires in order to retain talent, or attract talent. Both individuals and firms need the capability and flexibility to adjust the form of engagement in order to align to these changing conditions. Where, on the other hand, the firm faces declines due to market conditions they will need flexibility to change talent engagement from one form to another (eg from flat-fee compensation base to a performance-fee base). Further, as the skillset of the talent becomes mismatched with market needs, then flexibility will be needed to enable enhanced responsiveness through training and development but also through job and task modifications. Rules for engagement, disengagement and modification of engagement would need to support innovativeness, productivity and competitiveness.
Is there a positive benefit to aligning compensation systems to firm productivity ? (refer section 3, page 8 on Policy Document attached). On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ?
Are there empirical data to support your assertion ?
In Jamaica, unemployment among the 14-19 age group is reported as 49.0% and among the 20-24 at 33% (STATIN 2014 LFS). Paradoxically, these age cohorts represents the population of millennials and digital natives are hence are supposedly the most tech savvy segment of the population.
Rapid evolutions in ICT has resulted in radical changes in the nature of work. A mobile computing device, pervasive internet connectivity shortens the distance between demand and supply poles for certain types of work; particularly short-term service-type jobs aka micro-work or e-lancing. (refer section 7, page 11 on Policy Document attached).
On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ? Are there empirical data to support your assertion ?
In the context of a pre-existing labour force with 66% untrained and uncertified members, would expanding the pool of available talent in the labour force result in a positive productivity impact (refer section 2, page 7 on Policy Document attached). On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ? Are there empirical data to support your assertion ?
In a research project (https://www.researchgate.net/project/Mass-layoff-in-the-Argentinas-new-accumulation-regime-Psychosocial-consequences-and-critical-discourse-analysis_5753920d615e277e845c3dd5?_esc=profile) we are studying layoff consequences in Argentina.
For this project we need information (literature) about theoretical and empirical comparisson of two alternative methods of workforce intimidation: high unemployment rates vs. highly (mass media) emphasized collective layoffs (e.g. is a 20% unemployment rate as intimidating as 100,000 (temporally concentrated and mass media disseminated) layoffs, in a 7% unemployment rate economy?). Conservative governments apply both of them but recent examples of Latin American Countries (most of them with wage-led demand) confirm a bias towards the second.
Any suggestion will be very welcome!
Thanks a lot.
I'm looking for data on total labor costs (direct + indirect labor costs) for **specific products**. That is, how much a worker would cost a factory owner for producing, let’s say, a pair of jeans. These data could be from any country and industry you may have come across (garments, foods, electronics, etc. – anything really). Ideally, it’d be very helpful to have copies of factory timesheets; that is the list of steps, or operations, involved in producing let’s say a pair of jeans, whereas each operation is assigned a specific time. Thank you!!
I am searching for benefit and more developed methods used to determine the labor productivity in construction, and therefore i want to use this method in the perspective study and determine influencing factors.
I am looking for the possible labor market factors ( in addition to tight labor market) which affect the decision of a firm how to treat its employees. I would be glad if you suggest some related articles.
I would like for someone who can answer this question or give me some resources to the: Root cause of high unemployment in Mauritania?
I am planning to explore whether good HR practices (such as better employee treatment) can be used as tool to attract innovative & hardworking employees. Even though I have read several articles, I could not find articles which specifically explain that good HR practices (e.g. employee treatment) attract employees with desirable characteristics (innovative, hardworking, optimistic). Could you please mentions some articles which look into this matter?
For my research, I'm making an overview of types of flexible labour arrangements in different types of welfare states. Are there any suggestions on other types of flexible labor organization in other countries?
The concept of employability appears to be relatively new and has been variously characterised as comprising the three dimensions of career identity, personal adaptability, and social and human capital (Fugate 2004) as well as openness to changes at work, work and career resilience, work and career proactivity, career motivation and work identity (Hennekam, 2013). To the extent that it reflects “the individual’s ability to keep the job one has, or to get the job one desires” (Rothwell et al, 2007) does it provides an indicator of the efficiency and effectiveness of a labour market?
without having to suffer the problem of bias associated with endogeniety in a country like Nigeria
We investigate the matured workforce’ employment possibility from the point of view of the health by comparing relevant data of Czech Republic, Hungary and Austria. We used the method of correlation and regression (enter method) analysis to find the connection between the health/social contribution/benefit system related service data and employment.
In Austria the most important factors are social benefit (not unemployment, or housing or sickness related) 83.5%, the Death ischemic 96.2% diseases and the cancer 95.1% to the employment rate of older workers. In Czeh Republic and Hungary the employment rate of older workers could be explained by some kind of social expenditure, may be heritage of the previous political system, although in Czech Republic it results the highest rate of employment of this age group.
The Questions are: What could be the reason of Austrian data?
Way of life? Nutrition? Health service? Or something else?
The changing dynamics of the labour market imposes demands on the form and nature of the manifestation of collective action expressed in support of the holders/owners of talent (ie human capital). How are modern networks (unions, trade associations, professional bodies, guilds, etc) changing to be responsive, progressive and of value to members.
The objective of Labour Market Reform is to breathe modernity, dynamism and responsiveness into economies exhibiting labour-related competitiveness dysfunctions. Policies for reforming the Labour Market have far-reaching consequences on the productivity and competitiveness of an economy. The risk of implementing wrong and inappropriate policy can be grave. How do policy-makers ensure that their policy prescriptions are fit-for-purpose and will deliver the desired outcomes in terms of improved productivity and competitiveness at the firm level, sector level, industry level and national level? How can proposed reform policy measures be modelled and pre-tested for feasibility before being moved into an implementation phase ?
Does anybody know where it is possible to get good data on child labor in developing countries ? India and China are preferred but in general would be great to have cross section for most of the developing countries,many thanks
Data with respect to collective bargaining in steel sector within 2000 - 2014
Hello ResearchGate Community,
I really need your help for my Master Thesis. I am writing about dual career considerations in international assignments and want to find out if there are differences between Self-Initiated and Company-Assigned Expatriates.
I want to conduct interviews with dual career couples; six couples that relocated abroad on their own and six couples that went abroad within their organisations. If you have an idea how to find these interviewees or if you personally know someone that suits the criteria please let me know!
If you need more information on the exact interview format or anything else I am happy to provide you with more information.
Thank you in advance for any support you are able to provide!
Especially, social transformations with respect to social reproduction—including transformations to the measurement and valuation of domestic labor.
The publicly-available data on the Tanzanian statistical agency's website has information regarding household characteristics. But, there is no person-level data, i,e., detailed information about the individuals in the household such as their age, employment status etc. In contrast microdata from the earlier HBS (2007) contain person-level data.
I would appreciate any leads on how to obtain the person-level data from 2011-12 HBS.
It is believed that trade union power and density across countries is declining in the post-globalization period. I could not find any systematically compiled data in support or against this. Can you share data including research papers in this regard?
We have followed some 1,500 sophomore girls for about 15 years. They had the opportunity of applying for summer jobs at a Town council, and the applications were thereafter randomly approved by the council. Generally, the effect of a early work experience was significant. However, the sub-group of girls with low grades seemed to benefit enormously. Those that did not get an offer had an average, annual income of about SEK 100,000 (about $14,000) at the age of 30 years (15 years later). Those with an offer had about SEK 180,000 (about $26,000) at the same age later in life. The latter group's income is not far below national averages for the relevant age, whereas the former group's income is so low that it could hardly be collected from a full-time employment, albeit poorly paid. Unfortunately, the number of observations in the experimental study is in my opinion insufficient for any categorical claims. I therefore wonder if some one can offer an explanation to the result or point at other empirical studies in support of the seemingly extremely strong effect for this sub-group of girls? Details are in the attached manuscript.
I'm working on a research proposal, dealing with labor migration in the health and care sector. Interested in the situation in Japan, because it should be hit hard by the effects of demographic change. Any recommendations on literature?
For estimating a labour supply hours equation we use the after tax wage rate and IV regression. How wrong is it to use the gross wage rate and do a simple Tobit model?
I have a categorical independent variable (1-20) and based on theory it should have a positive sign in regression, i.e. larger category ID, larger dependent variable. although it could be nonlinear.
Except for treating it as continuous variable valued from 1-20 or use 19 dummies, is there any other method to test this variable has a significantly positive effect?
it's kind of like I use 19 dummies, then find a way to test the coefficients for these 19 dummies are significantly getting larger. In other words, I am testing the differences between each indicator and the referent group are increasing.
Thanks very much!
I am interested in analyzing the transfer from rentier sectors towards manufacturing sectors in Latin America, based on the reproduction schemes of Marx.
What is the appropriate measure of "labor productivity in agriculture" ? Can Population census data be used to obtain such measure? What is the official data source for labor productivity in agriculture? And how the total labor force in agriculture can be computed "more precisely" as the state level measure?
I am interested in knowing whether the “inverted-U” relationship between the degree of centralization in the collective bargaining and the unemployment rate is still valid. I am interested both in top research papers and in those ones with a more informative (less technical) aim.
Thanks in advance
The U.S. unemployment rate fell to 6.7% in December 2013 as labor force participation dropped to 62.8%. Many are arguing that the unemployment rate is not an appropriate measure of labor market slack because of falling participation. However, an examination of the relationship between quit rates and the unemployment rate (data on quit rates only through October) suggests that people are quitting their jobs at the usual rate that would be associated with an unemployment rate at around 7% (December quit rate data comes out in early February). The relationship between job openings and the unemployment rate (the Beveridge Curve) has been extensively studied and currently the unemployment rate is high relative to job openings (leading to arguments about loops around the Beveridge Curve). Is anyone aware of labor-market research on quit rates and unemployment?
In particular, I am interested in studying this link: thinking in the ability of collective action to affect the sustaining and elevation (defensive or offensive stage), of the wage floor.
I am looking for an index or indicators on the level of corporatism in Central and Eastern Europe for the most recent time-period, but I am finding it hard to find a source. If anyone is aware of such indicators, can you please let me know?
Has anyone worked on the issue or have any hints on what could explain such a phenomenon?
I am experimenting with the Oaxaca-Blinder decomposition to examine wage increases in Belgium between two years (2000 and 2010) using wage survey data. I am interested in the part of the wage increase accounted for by differences in socio-demographic factors between the two years (explained difference). My dependent variable is the log of hourly wage. However, there are lots of observations (too many to simply get rid of them) whose workload is very limited either because of part-time work or because they only lasted a short amount of time. Therefore, it seems to me that in addition to the survey extrapolation factors (pweight) I should also do some weighting according to workload. Does this make sense and how do you introduce an additional weight using the Oaxaca procedure in Stata (fweight and aweight do not seem to serve this purpose)?
In a case of binary dependent variable what is the best method, probit model or logit model, as today we have software's available and can easily calculate any of them.
Also is it necessary to work out marginal effect or odds ratios? As we are more concerned about probability so naturally signs matters most hear and the significance level.
It has become very common that papers focused on a great part of Labour Economics issues apply the Heckman filter in order to correct problem of supposed selection bias. However, I think that maybe it is not always necessary. Does anybody know any argument justifying not correcting for Heckman filter? More concretely, I am researching on housing tenure decisions of immigrant population living in host countries. To what extent is it necessary correct by Heckman filter when I run logit models for explain this kind of decisions?