Labour Economics Introduction: Some Preliminaries
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Labour Economics Introduction: Some Preliminaries
- Objectives of Labour Economics:
- To explain and evaluate labour market outcomes.
- Labour market outcomes?
- Compensation, wages, benefits, pay structure (price variables)
- Employment, unemployment, skill composition, types of jobs, hours worked (quantity variables)
- Other? union status; hiring and promotion practices; work rules; form, nature & length of contracts etc.
- Outcomes reflect the interplay of:
(1) decisions of buyers and sellers of labour services;
(2) institutions; and
(3) government.
1 - Role of Markets:
- Market economies: decision-making is largely decentralized.
-Decision makers: - individual buyers and sellers.
i.e. employers and employees (workers).
- Millions of workers are sorted into millions of jobs; thousands of wage rates.
- Wages, job matches, contract provisions reflect interaction of employers and workers.
- simple contracts: wage-hours provisions
- complex: contracts for long-term matches (wage progression, career paths, pensions and benefits)
- Explaining this process and its consequences is a major task of labour economics.
2 - Role of Institutions and Centralization:
- Main institutions: unions, professional associations and, in some countries, employer organizations.
- North American labour markets are among the most decentralized in the developed world.
- large non-union sectors
- decentralized bargaining within the unionized sector common.
- Many developed countries: more centralization
- union coverage higher
- bargaining often more centralized: industry or even economy-wide bargaining may occur.
- models and approaches needed for these arrangements too.
3 - Role of Government in Labour Markets:
- Markets, individual and union contracts are important but:
- they are highly regulated by government
- affected by many government programs.
- governments can be major employers.
- Studying the effects of government a key task.
- Government intervention in labour markets (Canada):
- Employment/Labour standards legislation (mainly provincial)
- Minimum wages - Minimum overtime premia - Maximum hours - Minimum vacation pay - Working age - Notice of layoff requirements - Maternity leave - Equal pay and pay equity - Health and safety regulation.
- Collective bargaining legislation (mainly Provincial) - regulates collective bargaining, union formation, strike/lockout rules.
- Public education and training programs. - helps determine workforce skill levels.
4 - Income Maintenance programs: - Workers' compensation (Provincial) - (Un)Employment insurance (Federal) - Social assistance or welfare (Provincial) - Public pension plans (Federal).
- Taxation: - income taxes affect sellers decisions - payroll taxes affect buyers decisions.
- Government as an employer (roughly 20% of employment)
- Public administration, health, education, social services, local government services, transportation, utilities all have significant public sector employment.
- More centralized: dominant employer, high unionization.
- Other countries?
- government involvement varies substantially
- more direct role in wage determination in some countries.
- active labour market policies in Sweden
- United States more laissez faire than Canada.
5 - The (micro) economic approach:
- Decision makers are assumed to be rational and self-interested.
- Implication: decisions are made based on a comparison of its benefits and costs.
- Best decision changes when factors determining the benefits and costs of the decision change.
- This approach underlies the models covered in the course.
- Is this realistic?
- Are people really like rational calculating machines?
- What about role of custom/tradition, altruism, notions of fairness in affecting decisions? Are these inconsistent with rationality?
- “Models” – simplification implied but hopefully captures something important.
- simplification: manageable, ignore unessential detail.
- Ultimate test? do the models make predictions that fit the data.
- Other possible approaches?
- Descriptive approaches: describe actual arrangements, their evolution. (Institutional economics; sociological approaches)
- Group behavior e.g. classes and conflict (Marxian approaches, Radical economics)
- Behavioral economics and psychological approaches.
6 - Some current issues in labour economics:
- Is current US unemployment and low employment structural or cyclical?
- Long-term unemployment: what are its long-term consequences?
- Aging populations and the workforce: implications? policies?
- New technologies and labour markets: polarization? what will people do? does AI mean no good jobs?
-Trade with China and India: what does it do to Canadian labour markets?
- Declining unionization: are private sector unions doomed?
- Inequality trends :
- why have the very rich gotten so much richer?
- what is happening to labour’s share of national income?
- Are high minimum wage rates a good idea?
- Can governments create jobs or do they just change the mix of jobs?
7 Data on Labour Market Outcomes: Major Sources
- Labour economics is “data intensive”.
- Good starting points:
Statistics Canada Web site: http://www.statcan.gc.ca
CANSIM Database (link off Statistics Canada’s main page): time series.
Lakehead library site: Data and Statistics (Government Info/Data), access to a variety of data sources.
See data source links on course website.
(1) Labour Force Survey:
- Monthly. See Labour Force Information Cat. 71-001.
- See course website for link to the latest release.
- Survey of roughly 62,000 households.
- Main source of data on: - Employment - Unemployment
- See questionnaire (in Guide to the Labour Force on website). Data includes:
- Hours of work - Industry - Occupation - Job tenure - Time unemployed - Reason last job ended, etc.
8 - Wage, union status and additional job data since 1997.
- Also provides information on worker characteristics. - Age, sex, education - Province, region.
- These can be cross-referenced with labour market outcomes.
- Historical LFS data.
- LFS has existed since 1946 (but major revisions).
- Labour Force Historical Review extensive tables for data back to 1976. (Access via Library webpage: Government Info/Data link then use “Equinox” or ODESI)
- Older data: Historical Labour Force Statistics (paper – Library) Historical Statistics of Canada (see below).
(2) Survey of Employment, Payrolls and Hours (SEPH)
- Monthly. See: Employment, Hours and Earnings Cat. 72-002
- Employer data: mix of administrative (tax data) and employer survey data.
- Data reported by detailed industry and province. - Number of employees - Hours of work - Weekly and hourly wages and salaries.
9 (3) Census:
- Every 5 years (since 1961 every 10 before that back to 1871).
- Wage and salary income, occupation and industry employment.
- Good personal and family characteristic data.
- Widely used in studies of wage differences and inequality.
- 2011 results are just being released ("National Household Survey")
(4) Survey of Labour and Income Dynamics:
- Predecessor: Survey of Consumer Finances
- A panel survey: follows same people over time.
- Annual data on incomes, poverty, inequality: Income in Canada
- Has a Statistics Canada page (search “Income in Canada”)
- Some tables with income, poverty data back to 1976.
(5) Historical Sources for Canada
Historical Statistics of Canada now online: (http://www.statcan.ca/english/freepub/11-516-XIE/sectiona/toc.htm)
CANSIM (see above) – has some historical data.
10 (6) U.S. Data:
- Data from the U.S. counterparts of the Labour Force Survey (Current Population Survey) and SEPH are reported in:
Employment and Earnings (paper) U.S. Bureau of Labor Statistics (BLS).
- BLS website: http://stats.bls.gov/ (data available free)
- Federal Reserve Economic Data (FRED) website: http://research.stlouisfed.org/fred2/
- many US and some international data series (electronic)
(7) International data
European Union (EUROSTAT): http://epp.eurostat.ec.europa.eu
International Labor Organization (http://laborsta.ilo.org/)
OECD (http://stats.oecd.org/)
Bureau of Labor Statistics: Foreign Labor Stats Page http://stats.bls.gov/fls/home.htm
11 Real and Nominal Wages
- In economic models the wage (compensation) variable is usually a measure of the real wage (real compensation).
Real wage = the wage adjusted for changes in the price level over time.
e.g.,
labour supply: workers likely care about what their wages will buy, i.e. compared to the prices of consumer goods.
labour demand: employers care about how the wage paid compares to the price of the product produced.
Measuring the Real Wage:
- Nominal wage data: wage in actual dollars
Retail worker in 1966: $1.00 hour
Retail worker in 2013: $10.25 hour
- These figures are not comparable over time.
- Inflation adjustment required.
- Real Wage: - nominal wage adjusted for changes in the price level.
- constant dollar wage, i.e., wage in terms of a base year.
12 - Calculating the real wage
(1) Obtain a relevant price index:
Consumer Price Index (Base year 2002) June 1966 17.5 June 2013 123.0
- Base year? year in which the index equals 100
- Prices in 2013 were more than 7 times higher (123/17.5) than in 1966.
(2) Convert the nominal wage data into CPI Base Year (2002) dollars:
Real Wage = (Nominal Wage) x (100/Price Index)
1966 $1.00 x (100/17.5) = $5.71 2013 $10.25 x (100/123.0)= $8.33
What if you want the real wage in 2013 dollars?
Real wage in = (Nominal wage) x (Price index in 2013) 2013 dollars (Price index)
- where the price index has 2002 as its base.
- so 1966 wage of $1 is worth $7.03 in 2013 dollars ($1x 123.0/17.5)
13 Measuring Economic Relationships: Ordinary Least Squares Regression
- References: see Ch. 1, Appendix of Benjamin, Gunderson, Lemieux & Riddell.
- Concerned with:
- Measuring the relationship between variables.
- Testing hypotheses about the measured relationship.
- Regression and related techniques are widely used in labour economics.
- Classification of Variables:
Dependent variable: the variable you are trying to explain.
Explanatory or independent variables: the variables you are trying to explain the dependent variable with.
14 Example: Wages and education.
Say that 12 people are surveyed and each is asked their wage and number of years of education. Say this is the result:
Person: Wage(W) Years of Education (ED) 1 $12.00 13 2 $24.00 17 3 $11.00 8 4 $15.00 12 5 $13.00 13 6 $20.00 16 7 $9.00 10 8 $10.00 6 9 $13.00 10 10 $15.00 14 11 $8.00 2 12 $9.00 3
- Scatter plot: plots the 12 observations of W vs. ED
- Suggests a positive relationship. - How to measure it?
15 - Linear Regression: assumes a linear relationship between the two variables.
W = a + b ∙ ED + e Eq. (1)
a = intercept or constant b = slope measuring the effect of a rise in ED on W
“a” and “b” are the coefficients or parameters of the regression.
“e” : error term (relationship is inexact due to measurement error, uncontrolled for variables, etc.)
- Choose a and b so that (Eq. 1) most closely fits the scatter pattern.
- Best fit? Method of ordinary least squares (OLS)
- OLS chooses a and b to minimize the sum of the squared, vertical distances between the fitted line and the data points.
(actual calculations done with statistical software)
For the example the best fitting line has: a=4.69, b=0.83
W = 4.69 + 0.83 x ED
- Interpreting output:
- Slope coefficient: an extra year of education raises the wage by 0.83 (83 cents).
- Intercept: if ED=0 predicted wage is $4.69
16 - Statistics commonly included in a regression output:
(a) Std. error of a, b: a measure of the uncertainty of the estimates.
The larger it is relative to the size of the coefficient (a or b) the less reliable is that estimate.
Example: std. error of a = 1.92 std. error of b = .17
(b) t-statistic:
t-statistic= (coefficient estimate) (Std. error)
- tests whether the coefficient estimate differs from 0.
i.e. tests for the existence of a relationship between the variables.
Example: t-stat of a = 2.44 t-stat of b = 4.88
- Rule of thumb (larger samples):
Absolute value of t > 2.0 relationship is statistically significant.
Absolute value of t<2.0 relationship not statistically significant.
- Output is sometimes presented with the t-statistics or std. errors in brackets below or beside the coefficient estimates:
e.g., W = 4.69 + 0.83 x ED (2.44) (4.88)
17 - R2 is a measure of goodness of fit.
- Range 0-1 : near 0 poor fit, near 1 close fit.
- it measures share of the variation in W that is explained by the estimated equation.
R2 = .704 , 70.4% of the variation in W (around its mean) is explained.
- Multiple Regression (more than one explanatory variable):
- In practice, the value of an economic variable depends on many variables.
- Multiple regression fits the relationship between a dependent variable (e.g. wage) and several explanatory variables.
e.g. Wage might depend upon: - Years of education (ED) - Ability (IQ) - Seniority (SEN) - Union status (UNION)
Multiple regression fits (still linear):
W = a + b x ED + c x IQ + d x SEN + f x UNION + e
by choosing: a,b,c,d,f to minimize the sum of squared deviations of the equation from the values of W.
18 - Importance of multiple regression?
- Simple version: did the estimate of "b" reflect education or omitted variables that are correlated with education?
e.g. education vs. ability
- Muliple regression allows you to isolate the effect of each explanatory variable on the dependent variable.
Dummy Variables:
- Dummy variable: has a value of 0 or 1
- Equals 1 if the observation satisfies a certain condition, 0 if it does not.
Examples: - Married or not - Woman or Man - Has a university degree or not.
- Coefficient on a dummy: shows the effect on the dependent variable of satisfying the condition vs. not satisfying it.
- Sometimes a series of dummy variables describe the same characteristic.
e.g., age, educational attainment, industry of employment.
- Say maximum educational attainment can be one of three possibilities and define a dummy variable for each possibility:
Less than high school LHS=1 (HS=MHS=0) High school HS=1 (LHS=MHS=0) More than high school MHS=1 (LHS=HS=0)
19 Notice that: LHS+HS+MHS=1 for any given person.
Say that wages (W) are determined as follows:
W = a LHS + b HS + c MHS
substitute: LHS=1-HS-MHS then
W = a (1-HS-MHS) + b HS + c MHS
so: W = a + (b-a) HS + (c-a) MHS
- In this last equation LHS=1 is the default category for educational attainment.
- Coefficients on HS and MHS are interpreted as the effect on W of being in either HS or MHS rather than the default category (LHS=1).
- Ordinary least squares is a common statistical method in labour economics.
- not the only method.
- output from many other methods can often be interpreted in much the same way as OLS.
- Handout: Earnings equation table from Krueger (1993)
- another standard way to present regression output.
- remember it is just a linear equation! (write out the equation for the example)
20 SUPPLY AND DEMAND IN LABOUR MARKETS
- Sources: BGLR, Ch. 1 and Ch. 7 pp. 191-202.
- Basic model of price and quantity determination.
Price of labour:
- wage rate (all compensation)
- Wages NOT income
- wage (W): price of labour per hour, per week
- income: wages and salary income plus all other forms of non-labour income (investment income, transfer income, etc.)
Income = W x (Time Worked) + Non-labour income
Measures of the quantity of labour
- Possible Units? Number of people Hours, weeks of work
- Time period: day, week, year.
- Level of “aggregation”? many possible levels of application
- Specific type of job.
- Related jobs: e.g - same occupations - same skill level
21 - Aggregate: - Across many (possibly all) job. - Demographic groups.
- Level of focus depends upon problem under study.
Labour supply (LS)
- The amount of labour time people in the relevant market are willing to work.
- Economic approach: a person’s labour supply decision reflects a comparison of the costs and benefits of supplying labour.
- benefit of supplying labour? Pay! - cost? Value of time in other uses.
- Some key determinants of labour supply:
- Wage rate
- probably a positive effect on LS
- higher pay: work more attractive vs. other uses of time.
- If pay is high in a particular type of job: people switch from alternative jobs.
- Wages paid at other jobs: value of time in another job.
- Tastes/preferences: determines value of non-work time, value of money.
- Size of the adult population: how many decision-makers?
- Labour supply curve - (Probably) upward sloping in wage (W)- LS diagram.
- Changes in values of determinants of LS , other than the wage, shift the LS-curve.
22 Labour Demand (LD)
- Amount of labour that employers in the relevant market would like to hire. .
- Economic approach? Labour demand decision reflects a comparison of the costs and benefits of hiring labour.
- cost? What the employer must pay the worker. - benefit? Value of the worker’s time to the employer e.g. value of output produced.
- Some determinants of labour demand:
- Wage level: - Negatively related to LD.
- Technology: determines how much labour is needed to produce a given amount of output.
- Output market conditions, e.g., output price.
- Cost or price of other inputs.
- Labour demand curve
- Downward sloping in wage (W)- LD diagram.
- Changes in values of other determinants of LD shift the LD-curve.
23 Labour Market Equilibrium
- Equilibrium: - values of W (wage) and L (labour) where LS=LD
- equilibrium? no pressure for W or L to change
- Call equilibrium wage W*
- Consider W - Excess demand for labour LS - labour shortage: employers rationed ; workers have no problems finding jobs - Workers: "pay more or I will go elsewhere". - Employers: some are willing to pay more rather than do without. - Result? Wage rises. - Consider W>W* - Excess supply of labour LS>LD - More job applicants than jobs. - Employers: "take less or I'll hire someone else" - Workers: some are willing to take less rather than be out of a job - Result? Wage falls. 24 - Is it a “good” outcome? Potentially “efficient”. - All jobs created are created because the employer and worker expect to gain i.e. benefits > costs to both decision-makers. - Each job match creates a surplus: At a given level of L: - Height of labour demand curve: maximum some employer in this market would pay for extra L. - Height of labour supply curve: minimum some worker needs to be willing to supply extra L. - Surplus on a given job? - Employer: difference between maximum would pay and the wage. - Worker: difference between wage and the minimum they need to be willing to work. - All jobs created at supply-demand equilibrium create some surplus for both employers and workers. - The supply-demand outcome generates the maximum amount of surplus from this market. (add up the surpluses from each job to get total surplus) - in this sense the outcome is a good or “efficient” one. 25 Usefulness of the supply-demand model: - Provides a framework for explaining wages and employment: - shifts in supply and demand curves change wages and employment. - levels of wages and employment reflect values of variables that shift supply and demand curves. - Imagine the Canadian labour market as a network of markets: - use it to think about wage structure, job share by skill & occupations. Limitations of the Supply-Demand model applied to labour markets: - Competition assumed: union sector? few employers? Public sector? - extensions needed! (will look at some of these) - No explanation of unemployment: excess supply disappears. - what's missing? Unemployment appears bounded but why doesn't it disappear? What explains fluctuations in unemployment? - Wages often seem more rigid than Supply-Demand suggests. - treats wages like any other price: adjusts to equate supply and demand. - Does the wage play other roles than just equating supply and demand? e.g. incentives, insurance, effects on morale? - Are wages locked-in with long-term employment relationships? i.e. is Supply-Demand only appropriate for short-term jobs or entry- level jobs? - Assumes away information problems - how do workers and employers find each other? (search models) - sorting and selection problems. 26 Application: Government Job Creation initiatives - Job creation initiatives may involve hiring more public employees or via grants or tax incentives that lead to private businesses expanding. - Supply-Demand perspective: both shift labour demand right. - size of horizontal shift in labour demand are job openings directly created by the initiative. - unless labour supply is perfectly flat actual change in employment is smaller than the horizontal shift in labour demand. - actual rise in total employment will be smaller the steeper is labour supply. - extreme? - if labour supply is vertical the policy creates no new employment. (policy moves fixed labour supply from other jobs into the new jobs created by the initiative: displacement ) - policy does raise wages if labour supply vertical. - what is more likely relatively flat or relatively vertical labour supply? Think about: - national labour market vs. localized labour market. - booming economy vs. depressed economy. 27 Application: R. Freeman (2006) “Labor Market Imbalances: Shortages, or Surpluses or Fish Stories” (see website) - How will the US labor market change over the next two decades? - he adopts a supply-demand framework. - Two major factors are often mentioned: (1) Demography: aging population and labour force, fewer young entrants, maybe eventually smaller workforce. - Will there be shortages? (Supply shifts left especially in market for entry positions) - Fewer workers, less output, smaller GDP likely. - Is this a big problem? - Supply-Demand model: wages will rise in affected markets. - this will eliminate shortages. - GDP may be lower but GDP per worker may rise! - Freeman doesn’t see this as much of a problem. (2) Globalization of the labour market: - A number of large countries have entered the world economy in recent years: - China, India, former Soviet Union. - Previously: little trade between these countries and the rest of the world. - Freeman: as if the global labour supply has doubled. 28 - Effect in US (or Canada): - Shift in labour demand left (some of the goods and services now produced in the new economies instead). - Pressure on wages to fall. - low-skill workers only? (he thinks not: Russian skill levels, Indian programmers, etc.) - But: prices of traded goods and services will fall too. i.e. real wages will fall less. - Employment in US? Not likely to fall much (overall labour supply close to vertical?) - Freeman thinks (2) not (1) is the bigger issue for the future. - Note: simple, some insights, uses only supply-demand. - Later section on labour demand: Katz and Murphy explanation of skilled- unskilled wage differentials is also an application of supply-demand. 29 ("race between education (supply) and technology (demand)")Appendix: An Algebraic Example of Supply and Demand LS = labour supply POP = population W= wage rate LD= labour demand ISPG = measure of income support program generosity PIND = output price index PK = price of physical capital - Variables whose values are determined in this market (endogenous): W, LS , LD - Variables whose values are taken as given, i.e. determined outside this market (exogenous): POP, ISPG, PIND, PK Say that these are the estimated Supply and Demand equations: Labour supply: LS = 400 + 25 W + 1.0 POP – 10 ISPG - POP, ISPG shift the labour supply curve, i.e. more POP more supply, more generous income support (↑ISPG) less supply. Labour demand: LD = 500 – 75 W + 30 PIND + 20 PK - PIND and PK shift the labour demand curve: higher output prices (↑PIND) more demand, higher price of capital (↑PK) more demand. Equilibrium: LS = LD (= L call L the equilibrium quantity.) 400 + 25 W + 1.0 POP – 10 ISPG = 500 – 75 W + 30 PIND + 20 PK Solve for the value of W (that equates supply and demand): W = (100 + 30 PIND + 20 PK – 1.0 POP +10 ISPG ) / 100 30 To get the equilibrium quantity of labour substitute the solution for W into either the labour supply or labour demand equation (doesn’t matter which since LS = LD at this wage): L = 400 + 25 W + 1.0 POP – 10 ISPG = 400 + 25 x {(100 + 30 PIND + 20 PK – 1.0 POP +10 ISPG ) / 100 } + .0 POP – 10 ISPG = 425 + 7.5 PIND + 5 PK + 0.75 POP - 7.5 ISPG Note: - The equilibrium levels of W and L depend on the shift variables (POP, ISPG, PIND, PK). - rise in POP or fall in ISPG shift the supply curve right – in diagram this will raise L and lower W (the same is true in the equations for equilibrium W and L) ; - rise in PK or rise in PIND shift the labour demand curve right: in a diagram this would raise the equilibrium W and L (same is true in the equations for equilibrium PIND and PK). 31