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feat(script): Shorten minimum wage laws section

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@ -338,60 +338,85 @@ though its focus remains primarily on regional trends rather than individual fac
### Minimum wage laws
@Chao2022, in a study looking at the effects of minimum wage increases on a country's income inequality, analyse the impacts in a sample of 43 countries, both LMIC and HIC.
Using a general-equilibrium model, it finds that there are differences between the short-term and long-term effects of the increase:
In the short term it leads to a reduction of the skilled-unskilled wage gap, however an increase in unemployment and welfare,
while in the long term the results are an overall decrease in wage inequality as well as improved social welfare.
It finds those results primarily stem from LMIC which experience significant effects driven by a long-term firm exit from the urban manufacturing sector thereby increasing available capital for the rural agricultural sector, while in HIC the results remain insignificant.
The study uses the Gini coefficient for identifying a country's inequality.
Some limitations of the study include the necessity to omit short-term urban firm exit for the impact to be significant, as well as requiring the, reasonable but necessary, prior assumption of decreased inequality through increased rural agricultural capital.
@Alinaghi2020 conduct a study using a microsimulation to estimate the effects of a minimum wage increase in New Zealand on overall income inequality and further disaggregation along gender and poverty lines.
It finds limited redistributional effects for the policy, with negligible impact on overall income inequality and the possibility of actually increasing inequalities among lower percentile income households.
Additionally, while it finds a significant reduction in some poverty measures for sole parents that are in employment, when looking at sole parents overall the effects become insignificant again.
The authors suggest this points to bad programme targeting, which at best has negligible positive impact on income equality and at worst worsens income inequality in lower income households, due to may low-wage earners being the secondary earners of higher-income households but low-wage households often having no wage earners at all.
A pertinent limitation of the study includes its large sample weights possibly biasing the impacts on specific groups such as sole parents and thus being careful not to overestimate their significance.
In a study on the impacts of minimum wage increases in Ecuador @Wong2019 specifically looks at the income and hours worked of low-wage earners to analyse the policies effectiveness.
The study finds that, generally, there was a significant increase on the income of low-wage earners and also a significant increase on wage workers hours worked which would reflect positively on a decrease in the country's income inequality.
At the same time, it finds some potential negative effects on the income of high earners, suggesting an income-compression effect as employers freeze or reduce high-earners wages to offset low-earners new floors.
Studies focusing on minimum wage effects further delineate themselves into ones that look at the effects on a national level such as @Wong2019, @Alinaghi2020 and @Chao2022,
and studies which specifically take sub-national spatial effects into account.
@Wong2019 specifically focuses analysis on the impacts on income and hours worked of low-wage earners,
finding that, generally, there was a significant positive effect on income and on waged workers' hours worked,
which can in turn reflect positively on the country's equitable income distribution.
At the same time, potential negative effects on the income of high earners are identified,
suggesting an income-compression effect as employers freeze or reduce high-earners wages to offset low-earners raised floors.
The findings hide internal heterogeneity, however:
For income the effect is largest for agricultural workers while for women the effect is significantly smaller than overall affected workers.
For hours worked there is a significant negative impact on women's hours worked, a fact which may point to a decreased intensive margin for female workers and thus also affect their lower income increases.
Limitations of the study include some sort-dependency in their panel data and only being able to account for effects during a period of economic growth.
Thus, while overall income inequality seems well targeted in the intervention, it may exacerbate the gender gap that already existed at the same time.
For hours worked there is a significant negative impact on women,
potentially pointing to a decreased intensive margin for female workers.[^wong-limits]
For income the effect is largest for agricultural workers,
while for women the effect is significantly smaller than the overall sample,
possibly also affected by the decrease in hours worked.
Thus, while overall income inequality seems well targeted in the intervention,
it may exacerbate the gender gap that already existed at the same time.
[^wong-limits]: The study can only analyse effects during a period of economic growth for the country, which, combined with some sort-dependency in the panel data, may introduce a form of unobservable exogenous bias into this finding.
@Chao2022, looking at the effects in a sample of 43 countries including LMIC and HIC,
find strong short-term and long-term differences in outcomes:
In the short term minimum wage introductions lead to a reduction of the skilled-unskilled wage gap,
however an increase in unemployment and welfare,
while in the long term the results are an overall decrease in wage inequality as well as improved social welfare.[^chao-indicator]
It finds those results primarily stem from LMIC which experience significant effects driven by a long-term firm exit from urban manufacturing sectors,
thereby increasing available capital for the rural agricultural sector,
while in HIC the results largely remain insignificant.
Some limitations of the study include the necessity to omit short-term urban firm exit for the effects to remain significant,
as well as requiring the prior assumption of decreased inequality through increased rural agricultural capital.
[^chao-indicator]: To identify the overall income inequality within the countries, the study primarily utilizes the Gini coefficient.
@Alinaghi2020 conduct a microsimulation to estimate the effects of a minimum wage increase in New Zealand on overall income inequality and further disaggregate along gender and poverty lines.
It finds limited redistributional effects for the policy, with negligible impact on overall income inequality and the possibility of actually increasing inequalities among lower percentile income households.
The authors caution against overestimation of the results' generalisability due to large sample weights possibly biasing results towards sole parent outcomes.
While the effects on poverty measures overall also remain insignificant for sole parents,
it does find significant poverty reduction for sole parents which are in employment.
The authors suggest these findings point to bad programme targeting,
which at best has negligible positive impact on income equality and at worst may worsen income inequality for lower income households,
as low-wage earners are often the secondary earners in higher-income households but low-wage households often have no wage earners at all.
Looking at the effect of increases in Romania,
@Militaru2019 find that minimum wage increases generally correlate with a small wage inequality decrease,
and also carry a larger positive impact for women.
They identify a two-fold mechanism which increases the number of waged workers in the total number of employees and mainly concentrates benefits for workers at the minimum income level.[^militaru-limits]
They also suggest this being the probable channel for larger impacts on female workers since they make up larger parts of low-income and minimum wage households in Romania.
[^militaru-limits]: One limitation of the study may be the over-representation of employees in the sample, as well as not being able to account for tax evasion or other behavioural changes in the model.
<!-- non-spatial policy but spatial effects -->
@Gilbert2001 undertake a study looking at the distributional effects of introducing a minimum wage in Britain, with a specific spatial component.
Overall it finds little effect on income inequality in the country.
It finds that the effects on rural areas differ depending on their proximity to urban areas.
While overall income inequality only decreases a small amount, the intervention results in effective targeting with remote rural households having around twice the reduction in inequality compared to others.
Rural areas that are accessible to urban markets are less affected, with insignificant impacts to overall income inequality reduction.
One limit of the study is that it has to assume no effects on employment after the enaction of the minimum wage for its results to hold.
Turning to studies which take into account spatial effects between different regions,
@Gilbert2001 similarly find insignificant effects on income inequality in the UK,
agreeing with the results of @Chao2022.
However, the effects for rural areas differ depending on their proximity to urban areas.
While rural areas which are accessible to urban markets are less affected resulting in similarly insignificant impacts,
more remote rural households experience almost double the reduction in inequality,
which the authors argue points to effective targeting of the policy.
For the results to hold, the study has to assume no significant effects on employment after the enactment of the minimum wage.
In a study on the impacts of minimum wage and direct cash transfers in Brazil on the country's income inequality,
@SilveiraNeto2011 especially analyse the way the policies interact with spatial inequalities.
It finds that incomes between regions have converged during the time frame and overall the cash transfers under the 'Bolsa Familia' programme and minimum wage were accounting for 26.2% of the effect.
Analysing both the effects of minimum wage and direct cash transfers in Brazil,
@SilveiraNeto2011 also focus on the spatial impacts within the country.
Incomes between regions have converged during the time frame and overall the cash transfers under the 'Bolsa Familia' programme and minimum wage are identified as accounting for 26.2% of the effect.
Minimum wage contributed 16.6% of the effect to overall Gini reduction between the regions while cash transfers accounted for 9.6% of the effect.
The authors argue that this highlights the way even non-spatial policies can have a positive (or, with worse targeting or selection, negative) influence on spatial inequalities,
as transfers occurring predominantly to poorer regions and minimum wages having larger impacts in those regions created quasi-regional effects without being explicitly addressed in the policies.
Some limitations include limited underlying data only making it possible to estimate the cash transfer impacts for the analysis end-line,
and minimum wage effects having to be constructed from the effects wages equal to minimum wage.
The authors argue that this highlights the way even ostensibly non-spatial policies can have a positive
(or, with worse targeting or selection, negative) influence on spatial inequalities,
as transfers occurring predominantly to poorer regions and minimum wages having larger impacts in those regions created quasi-regional effects without forming explicit part of the policies.[^silveiraneto-limits]
@Militaru2019 conduct an analysis of the effects of minimum wage increases on income inequality in Romania.
They find that, generally, minimum wage increases correlate with small wage inequality decreases, but carry a larger impact for women.
The channels for the policies effects are two-fold in that there is an inequality decrease as the number of wage earners in total number of employees increases,
as well as the concentration of workers at the minimum level mattering --- the probable channel for a larger impact on women since they make up larger parts of low-income and minimum wage households in Romania.
Limitations to the study are some remaining unobservables for the final inequality outcomes (such as other wages or incomes), the sample over-representing employees and not being able to account for any tax evasion or behavioural changes in the model.
[^silveiraneto-limits]: For the analysis, minimum wage effects had to be constructed from the effects that wages equal to the minimum wage had, and cash transfer impacts could only be estimated for the end-line analysis.
@Sotomayor2021 conducts a study on the impact of subsequent minimum wage floor introductions on poverty and income inequality in Brazil.
He finds that in the short-term (3 months) wage floor increases reduced poverty by 2.8% and reduced income inequality by 2.4%.
Over the longer-term though these impacts decrease,
the minimum wage increases only show diminishing returns when the legal minimum is already high in relation to median earnings.
It suggests that additional unemployment costs, created through new job losses through the introduction, are offset by the increased benefits --- the higher wages for workers.
The authors also suggest an inelastic relationship between increases and poverty incidence.
One limitation of the study is the limit of tracking individuals in the underlying data which can not account for people moving household to new locations.
The data can only track individual dwellings --- instead of the households and inhabitants within --- and thus resembles repeated cross-sectional data more than actual panel data.
On the other hand also in Brazil, @Sotomayor2021,
looking at the poverty and inequality outcomes of subsequent minimum wage floor increases,
finds a poverty reduction by 2.8% and income inequality reduction by 2.4% in the short term (3 months).
In the long term the results largely agree with @SilveiraNeto2011,
finding that minimum wage increases show diminishing returns where the legal minimum is already high in relation to median earnings.
Overall the study finds additional unemployment costs --
created through new job losses through the introduction --
are offset by the increased benefits found in higher wages for workers.
The author suggests an inelastic relationship between increases and poverty incidence,
with the limitation that the data can only track individual dwellings (instead of household connected to their inhabitants) and thus both resembles repeat cross-sectional data more than panel data,
and is not able to account for people or households moving to new dwellings.
### Collective bargaining