WT week 3 development with unlimited supplies of labor Flashcards
Motivation
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
Examines how underdevelopment itself exacerbates productivity risk for the poor. How a productivity shock causes larger changes in wage if workers are closer to subsistence, less able to migrate, and more credit-constrained because workers supply less elastic labour.
Special settings
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
Majority of world’s poor work in agriculture, which is prone to seings in productivity due to shocks (i.e. drought). Effect on real wage has knock-on effects, i.e. increase malnuturition, school drop-out rates, farmers having to sell-down their assets which decreases future income. A less developed financial sector prevents consumption smoothing.
Theory
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
“Labour supply response to fall in wage has offsetting IE and SE. Wage fall causes IE which causes increase labour supply and SE which shifts away from labour. Stronger IE in underdeveloped countries due to inability to save/borrow; poverty also increases IE as higher marginal utility for someone closer to subsistence. Also impacted by inability to easily migrate between areas. Causes for IE>SE, so labour supply increases.
General equilibrium wage caused by inelastic labour supply makes poor worse off as their labour becomes more volatile (in the case of a productivity shock). “
Empirical design
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
“Models agrarian economy where amount of land owned by each individual varies, and equilibrium wage is determined by indidividual labour supply and demand decisions
Models responsiveness of equilibrium wage to TFP shocks with the variance of workers’ ability to smooth consumption and how it differentially affects welfare of wealthier versus poorer people
Tests predictions using data on 257 districts in India (1956-1987); data on agricultural wage and crop yield used to estimate elasticity of wage wrt TFP. Then testing whether wage elasticity is larger in areas that are less developed
Isolate exogenous changes in agricultural productivity by using local rainfall as instrumental variable”
Data
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
“Panel data on 257 rural districts, defined by 1961 boundaries, observed from 1956-1987
Sample covers 80%+ of India’s land areas, including major agricultural regions
District-level male agricultural wage taken and crop yield from World Bank india Agriculture and Climate dataset
Rainfall from Center for Climatic Research at Uni of Delaware
Four types of district traits examined: financial services, access to other areas, poverty and landownership (taken from different sources)”
Key findings
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
“Wage is less sensitive to productivity shocks if area has better opportunities for shifting income intertemporally (i.e. if banking sector is more developed)
Access to other areas which enables workers to substitute away from home labour market, leads to large reductions in wage variability
Comparing to sample mean, a standard deviation increase in railway access reduces the wage elasticity by more than 50%
Landlessness among agricultural workers decreases the responsiveness of the wage to TFP
Data might suggest that the landless migrate in response to negative shocks more readily than landowners who are tied to their land”
Interpretation / policy implications
Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries (Jayanchandran, 2006)
“Emphasises locally aggregated risk, i.e. when a village suffers a drought, all suffer in tandem. Openness could help alleviate this kind of risk, i.e. labour force mobility dampens effects of shock if workers in low-productivity areas migrate to higher-productvitiy areas
May be the poor who especially benefit from this type of market integration
- an improvement in financial services could do more harm than good for landowners since they then have to pay workers a higher wage in bad times
- land redistribution from the rich to the poor could have counterintuitive effects. If land redistribution decreases outmigration, it could have a negative pecuniary effect on individuals who remain landless”
Motivation
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
To test for downward nominal wage rigidity and whether it affects employment.
Special settings
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
Labour is mostly in agriculture, mostly casual labour. There is a salient prevailing wage at any given point in time within a village. Rainfall generates shocks to production. Wages are negotiable between worker and employer, so reflect market conditions. The survey results show that nominal wage cuts are seen as unfair.
Theory
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
Rigidities may prevent wages from adjusting fully to shocks, with potentially important consequences for employment, earnings, and output. For example, if wages do not fall during negative shocks, this may increase layoffs—deepening the impact of recessions and exacerbating business cycle volatility. In addition, the labor rationing generated by rigidities could give rise to “disguised unemployment” or “forced entrepreneurship”, creating a misallocation of labor across firms
Empirical design
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
“Model a small open economy with decentralized wage setting and exogenous product prices. Rigidities arise because workers view nominal wage cuts as unfair and retaliate to such cuts by decreasing effort. Firms make decisions only taking into account current period payoffs.
The identification strategy: response of wages to transitory shocks generated by rainfall in current and following period. Assumptions: rainfall shocks are transitory: monsoon rainfall affects total factor productivity (TFP) in the current year but does not directly affect TFP in future years; shocks are uncorrelated with other determinants of wages; shocks are serially uncorrelated.”
Data
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
“600 Indian districts from 1956-2009. Shock is deviation of rainfall from mean.
- World Bank Agriculture and Climate dataset, which provides yearly data on 240 Indian districts in 13 states from 1956-1987 - The unit of observation is a district-year
- Rainfall data is taken from Terrestrial Precipitation: 1900-2008 Gridded Monthly Time Series constructed by the Center for Climatic Research, University of Delaware”
Key findings
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
“Wages adjust upwards but not downwards. Relative to no shock, wages are higher if there is a positive shock and no lower if there is a negative shock. (Table 1, col. 1 and 4)
There is a ratcheting effect: if a period with a positive shock is followed by a non-negative shock, wages stay at the higher level.
Ratcheting causes unemployment: in the period after a positive shock, employment falls by 9%.
Inflation mitigates rigidity and ratcheting:
when inflation is higher, nominal and real wages are lower under negative shocks than when there is no shock - allows for downward adjustment;
when inflation is higher, real wages are more likely to fall during droughts and after transitory positive shocks;
when inflation rises, positive shocks are less likely to have persistent effects on current wages - mitigates ratcheting;
increase in real wages in current period is unaffected.
Table 4: a positive shock in the previous year lowers agricultural employment in the current year.
In the year after a positive shock, while the landless experience the largest decrease in wage employment (1.198 days/week), small landholders also experience an estimated decrease of 0.444 days/week or 22%, but large landowners` labor supply is largely unaffected by lagged positive shocks; this makes sense since these households do not sell much labor externally.
Ratcheting distorts firm size and misallocates labour: small landowners are the primary suppliers of agricultural labour, due to ratcheting, they lose their job; in response, they increase labour supply to their small business, so number of small businesses increases. Rigid wages are due to fairness norms:
workers perceive wage cuts as violation of fairness norm;
employers fear workers reduce effort in response to wage cut;
inflation-induced wage cuts not seen as unfair.”
Interpretation / policy implications
Nominal Wage Rigidity in Village Labor Markets (Kaur, 2019)
“Two categories of potential concerns.
The first is a violation of the assumption that shocks are transitory (rainfall improves soil and leads to higher output in current and following period), this would explain ratcheting. But then employment should also be higher next period and inflation should not reduce persistent effect.
The second is that rainfall affects labor supply or demand through other channels (OVB), such as migration or capital accumulation. Shocks affect worker quality: positive shocks lead to hiring of better workers, who are retained next period. Shocks affect labour supply: positive shocks lead to higher migration so wages rise and employment falls next period. Shocks enable capital accumulation: small farmers can now invest in capital and decrease future labour demand. But OVBs inconsistent with inflation response.
Spurious effects: if inflation and adoption of irrigation (reduces sensitivity to rainfall) trend upward over time.
External validity: in other settings wages less reflective of market conditions, fairness norms could be context-specific.
Policy implications:
particularly relevant for developing country labour market;
volatility means that labour markets do not adjust fully and therefore production is not at the frontier;
landless and marginal farmers, the poorest and most vulnerable workers, bear the most of the labour market effect.”
Theory
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
The provision of a small amount of money to subsistence farmers in randomly selected villages in Zambia can prevent hungry season and reduce the need for farmers to sell their labour to other farmers, which in turn reduces their own output for the following harvest
Motivation
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
To examine the effect of providing a small amount of additional income to households during the hungry season.
Special settings
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
“Low-income households in agrarian economies rely on the money from harvest season to last for the entire year, making the months prior to harvest the most time of year. Would have used up all savings but the income from future harvest is still a while away. Entire annual income often comes from a single paycheck. Strong cyclical and seasonality given everyone in the neighbourhood would suffer at the same time. Find that people currently sell their labour to other farmers to buy urgent goods. No access to credit markets for these farmers as all friends/neighbours who they might informally lend from are also cash-strapped. Saw interest rates of 100%+ monthly.
Currently seen that the majority of inefficiency in the market is due to poorer families selling their labour (transfer from poorer to richer)”
Empirical design
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
“Grant lower-cost loans during hungry season to a group of subsistence farmers at a level that is enough to get through hungry season (equivalent of 3 bags of maize)
2 treatment groups; one in form of maize and other in form of cash, to understand if there’s a difference in the modality of the loan (issue of transportation costs versus inefficient use of cash)
Offered at start of hungry season (January) with repyament at harvest in July”
Data
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
“Household surveys collected during both years of experirment (baseline, midline, harvest) with ongoing labour surveys and a final endline survey
Surveys on labour activities, consumption, farming practices”
Key findings
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
“By selling own labour to others, they are then underinvesting in their own harvest which has an impact on future income (a form of consumption smoothing not through borrowing)
No notion of misuse of cash, often being used to reallocate labour (either selling their own labour less or buying the labour of others) –> re-investment into their farm
Found harvest increased by 9% which covered the value of the loan on average
No long-term effect seen on the following years
Aggregate effect if offered to all farmers would likely be re-distribution as would help poorest farmers as sell their own labour less, but less labour input for the richer farmers –> also increases wages so have to work less for same subsistence amount”
Interpretation / policy implications
Seasonal Liquidity, Rural Labor Markets, and Agricultural Production (Fink, Kelsey Jack and Masiye, 2020)
“Extremely high take-up rate when compared to traditional microfinance programmes (98%); focuses on consumption rather than capital accumulation
Presents an untapped market for provision of credit to rural individuals (as opposed to businesses)
Welfare gains from relaxing seasonal liquidity constraints
Scaling access to lower interest rate loans leads to larger wage adjustments and more homogenous returns to labour within the village, results in greater reductions in income inequality
Bundling seasonal loans with other technologies (i.e. digital borrowing platforms) might help bring down costs
More secure savings may also decrease reliance on family labour as a costly smoothing strategy”
