Readings LT Flashcards
(45 cards)
(Does Management Matter. Bloom et al)
Special setting and data specifics?
It’s set in India looking at large, multi-plant textile firms.
Treatment plants receive 5 months extensive management consulting from large int. consulting group.
Data compiled from direct observation at the plant/factory
For non-project firms, data was collected during the interview from direct factory observation and discussion with the managers.
(Does Management Matter. Bloom et al)
Empirical design?
66 potential subject firms with 34 expressing interest in project and 17 committing to consulting program.
11 treatment firms with 14 treatment plants and 6 control firms with 1 control plant
Consulting treatment had 3 phases (diagnostic, implementation and measurement)
Estimate the impact of consulting services on management practices via ITT equation. ***** GO OVER
(Does Management Matter. Bloom et al)
Key findings?
Improvement of management practices in treatment plants. Control plants also improve slightly after diagnostic phase and even non-experimental plants in treatment benefit (evidence of cross-plant learning).
Improvements in management led to ++ productivity (from ++ quality and ++ efficiency and reduced inventory) Also followed by longer-run increase in firm size - no plants per firm is higher for better managed firms.
No sig change in invetory during implementation phase - it was only post treatment it was reduced.
Same for output where it increased after.
Profits per plant +++
Major initial barrier was information about whether the practices would be profitable which is why they didn’t take them up initially.
(Does Management Matter. Bloom et al)
Conclusions drawn?
Intervention v expensive for free consulting.
Not strong external validity (other industries, countries)
Firms weren’t implementing changes due to lack of info so maybe should focus on training programs for basic operations management to improve firms productivity
Policies could maybe deal w what may be source of poor management practices (reduce barriers to competition, improve legal/regulatory system to reduce reliance on social capital for trust in management)
(Retail globalization and Household welfare. Atkin et al)
Special setting/Data?
Mexico where no. foreign supermarkets close to quadrupled from 2002 to 2014.
Data on store locations and dates of opening from Mexico’s national association of retail business.
Monthly micro data (price quotes) to create Mexican CPI
The consumer panel micro data of large international market research company.
Also uses Mexican Nat Income & expenditure surveys to view income and sources of income for each houses + expenditure.
(Retail globalization and Household welfare. Atkin et al)
Empirical design?c
Expression: Change in household welfare due to retail FDI on household welfare in the municipality of entry. Decompose this into 6 main channels to find the total welfare effect:
- effect on consumer prices at pre-existing domestic retailers
- effect due to exit of domestic retailers
- all consumer gains derived from being able to shop at foreign store itself
- retail labour income effect
- retail profits effect for domestic store owners
- indirect effect on other sources of household income from nonretail sectors of local economy
Then use household-level income shares by occupation/sector and consumption shares across products/stores to estimate remaining key parameters.
Combine the estimated effects and estimated parameters and the expression to quantify welfare effects of foreign entry for every household and obtain full distribution of welfare effects across households.
Change in welfare due to entry of foreign supermarket expressed as compensating variation (CV) for each household h in municipality of entry.
CV - change in exogenous income necessary for a HH to maintain same utility when a foreign retailer arrives between period 0 and 1
(Retail globalization and Household welfare. Atkin et al)
Key findings?
Prices:
- foreign stores charge 12% lower prices for identical bar codes compared to domestic retailers
Quality:
- foreign stores offer product mix significantly higher quality
Expenditure:
- foreign stores capture more than 30% total household retail expenditure after entering
Distribution effects:
- richest income groups substitute much more of their retail consumption in foreign stores than poor
- large welfare gains for average household which is driven by reduction of cost of living
Effect on domestic retailers:
- negative significant effect on no. of them and also on their profits
(Retail globalization and Household welfare. Atkin et al)
Conclusion?
Retail v important for employment, production and consumption in developing countries
Development should focus more on the services sector
(The Effects of Rural Electrification on Employment. Dinkelman)
Special setting?
South Africa where grid infrastructure was rolled-out and was rapid and extended in rural areas targeting low capacity households instead of industrial users.
(The Effects of Rural Electrification on Employment. Dinkelman)
Data?
Panel dataset of community aggregate variables using 1966 and 2001 South African census data and also: spatial data on local of electrification infrastructure, administrative data on project placement and also measures of geography at baseline.
Unit of analysis for IV strategy is community-year.
(The Effects of Rural Electrification on Employment. Dinkelman)
Empirical design?
- Instrumenting for project placement with land gradient.
- identification strategy: higher gradient raises ave cost of household connection so gradient is an important factor for prioritising areas for electrification but it doesn’t effect employment growth independently - Fixed effects strategy
- to estimate labour market effects using only within-district variation: construct 4-period panel of magisterial districts from cross-sectional household survey data and address non-random project placement and confounding economic trends by directly controlling for magisterial district fixed effects and trends
(The Effects of Rural Electrification on Employment. Dinkelman)
Key findings?
First stage:
- as gradient increases the probability of receiving Eskom Project falls across columns and size of this coefficient doesn’t change much with more controls whilst the precision improves
Employment:
- Female employment increases with electricity project: positive coeffs on poverty rate, sex ratio, female-headed households shows fem employment rises faster in poorer places.
- Male employment rises but not significant.
- frees up women’s time for the market
- could be driven by migration behaviour to electrified places
Electric lighting:
- rises in community with electricity project
Home production:
- cooking with electricity rises
- areas chosen to be electrified because of flatter gradient use electric lighting much more and cooking with wood falls a lot here
(The Effects of Rural Electrification on Employment. Dinkelman)
Conclusion?
- limited external validity - these effects should be interpreted in existing economic conditions of South Africa at the end of Apartheid
- such infrastructure projects likely to increase quality of life and contribute to economic development
(Political Economy of Deforestation in the Tropics. Burgess et al)
Special settings?
Indonesia where it has the largest strands of tropical forest and experiences rapid deforestation.
Also is the 3rd largest producer of greenhouse gases worldwide.
Indonesia also experienced remarkable increase in the no. of administrative divisions over the past decade after the collapse of New Order regime.
(Political Economy of Deforestation in the Tropics. Burgess et al)
Data?
- so much deforestation is result of illegal logging so dataset is constructed from satellite imagery (430 image inputs for each 250by250 pixel used to estimate forest cover loss per year for that pixel)
- dataset combined with data on district boundaries and land-use classifications
- use official data for prices because it will be formed by both legal and illegal supply
(Political Economy of Deforestation in the Tropics. Burgess et al)
Empirical design?
- estimate fixed-effects: Poisson quasi-maximum likelihood count model
E(deforest) = province fixed effect + exp (bnumdistrictsinprov + islandxyear fixed effect)
Coefficient b represents semi-elasticity of deforestation with respect to number of districts in the province
Why use Poisson QML than log dependent variable w OLS?
- there are observations where dependent variable = 0 so a count model is more appropriate
OLS regression
- run price/quantity on numdistrictsin prov and fixed effects of wood type by province and by island by year
Examining SR impact of oil and gas rents on illegal logging?
- Same poisson equation but this time PerCapOilandGas inside the exponential
(Political Economy of Deforestation in the Tropics. Burgess et al)
Key findings?
Deforestation rate:
- increases if an additional district is formed within the province
Contemporaneous effect:
- adding one additional district in a province decreases prices and increases quantity of logs felled though the impact on prices is not stat sig
- after 3 years, impact on prices is sig
- estimate demand elasticity of -2.27
Logging and oil and gas rents:
- each $ of oil and gas rents received reduces logging by 0.3% in ST
- in medium run, oil and gas rents and rents from logging are no longer substitutes
- rents from illegal logging and rents from oil and gas revenue sharing are substitutes only in SR and in medium run over half this effect disappears
(Political Economy of Deforestation in the Tropics. Burgess et al)
Conclusions?
Increasing no. of political jurisdictions is not merely driven by changes in allocation of legal cutting rights but is also due to something happening with regard to illegal logging as well
TO counteract corruption:
- strengthen top-down monitoring and enforcement eg increase prob of detection of illegal activity
- provide district gov w alternative sources of rents
(Weather, Climate Change and Death in India. Burgess et al)
Aim?
Testing whether population at different stages of development are affected differently by same weather variation.
(Weather, Climate Change and Death in India. Burgess et al)
Special setting?
Rural vs urban regions in India. Former is predominantly agricultural employment and latter is non-agric
India primarily a rural country (72% in 2000)
(The Digital Provide. Jensen)
Special setting?
Set in Kerala where fishing is an important industry and mobile phone service was gradually introduced from 1997 and by 2001. Over half were using mobile phones to coordinate sales.
(The Digital Provide. Jensen)
Theory?
ICTs may help poorly functioning markets work better and thereby increase incomes and/or lower consumer prices.
Two principles underpin functioning of the market economy:
- 1st fundamental theorem of welfare economics (i.e., competitive equilibria are Pareto efficient)
- The Law of One Price (i.e., the price of a good should not differ between any two markets by more than the transport costs between them)
(The Digital Provide. Jensen)
Identification strategy?
Paper exploits region-by-region rollout of mobile phone coverage in the Indian state of Kerala. No pre-existing differential trend in market outcomes across regions and no other factor could have influenced outcome changes differently across regions
(The Digital Provide. Jensen)
Empirical method?
Two towns with identical number of fishermen
- Fisherman’s catch (x) is a random variable with an identical distribution across individuals and depends on the density of the fish (d)
- Each zone can either be in a high- or low-density state
- On observing their own catch, each fisherman updates their assessment of the state of their catchment zone: a higher catch induces a switch to a non-local market despite paying the transportation costs (this is because of higher expected gain in profits for an expected price difference)
- In a high density state, greater supply will reduce price dispersion in a given market significantly.
There’s also a search technology: where for a cost, fisherman can learn about the catch in both zones and avoid unprofitable switching. This is purchased up to the point where expected gain from arbitrage equals cost of search
Waste arises when the max quantity demanded is less than the total catch
Measuring welfare:
Producer welfare is change in profits (fixed costs don’t change + inelastic supply)
Consumer welfare is change in consumer surplus from an estimate of the consumers’ demand curve (pre- and post-mobile) and consumer retail