Higher wages or more jobs to reduce poverty?

There is a somewhat twisted consensus around the fact that minimum wages do little about poverty, and also have no effect on employment. Why then would we raise them?

Poverty, for many, is a household concept. The loss of income by any family member will pull all family members into poverty. This is of course true and the impact of minimum wages on career interruptions is difficult to establish causally.

However, another line of reasoning would be to wonder what wage structure would exist if the labour market was entirely unregulated. It is obvious that just about any job might exist, if there would be no drawback position such as social security, and low reservation wages. In the current globalized economies, this is very likely. In more remote, nordic economies, this used to be less so. Combining high schooling and high bargaining coverage and unionization, in-work poverty has not been a challenge.

Besides migration and the downgrading of the workforce, the pressure on benefits, and hence the lowering of the reservation wage, technological change and in particular job polarization is also fuelling the growth of the low wage segment.

If we look at the role of wages in reducing poverty in the past, this is perhaps not as important as it will be in the future.

Beter één enkelvoudig statuut

In België blinken we uit in bijbouw: er zijn vele institutionele tuinhuisjes opgericht voor arbeiders, bedienden, uitzendkrachten, vaste contracten, vaste benoemingen, aanstelling bepaalde duur, studentenarbeid, flexi-jobs, etc. Ze hebben een verschillend ontslagrecht en opzegtermijnen, verschillend vakantiegeld, verschillende sociale bijdragen, en noem maar op. Het resultaat is dat een standaardovereenkomst ontmoedigd wordt én voor investeerders zeer oninteressant lijkt. België heeft dus ogenschijnlijk een hoge belastingdruk, die weliswaar ontsnapt door de achterpoortjes van de tuinhuisjes.

Waarom kan het niet eenvoudiger, met slechts één type arbeidscontract, dat gelijk is voor arbeiders, bedienden, ambtenaren en uitzendkrachten? Er is één type opzegtermijn dat in onderlinge overeenkomst kan worden bijgesteld. Uitkeringen volgen automatisch en zijn afhankelijk van het aantal gewerkte uren. Dit zou ongelofelijk veel administratie en fouten voorkomen, zonder aantoonbare nadelen. Uitzendkrachten of studenten krijgen precies hetzelfde contract en betalen dezelfde bijdragen, en kunnen zo tien contracten bij hetzelfde bedrijf hebben in twee jaar tijd, en een maximum van twee jaar werk voor een bedrijf, waarna geen nieuw contract meer kan worden gesloten. Wil men uitzendarbeiders vaker inschakelen, dan kan dit mits een standaardcontract met het uitzendkantoor.

Dit zou de grootste flexibilisering van de Belgische arbeidsmarkt zijn, terwijl het de werknemers net méér zekerheid biedt en de bedrijven transparantie.

Belastingsdruk nergens zo hoog als in België

Een commentaar op een terugkerende klassieker: "Belastingsdruk nergens zo hoog als in België". https://www.vrt.be/vrtnws/nl/2018/04/26/belastingdruk-nergens-zo-hoog-als-in-belgie/

Ik vraag mij af wat de zin is van zulke statistieken waar men je mee om de oren slaat. Stel dat men zou zeggen: nergens in de wereld kosten tractors zoveel als in België. Dan zou men denken: dat moeten goede tractors zijn, de landbouw zal daar wel productiever zijn in vergelijking met andere landen, of nog: daar worden schijnbaar mooie winsten geboekt om die tractors te kunnen aankopen. Dat zou goed nieuws zijn.

Hoge belastingen, want een dure overheid, dat wordt geframed als slecht nieuws. Misschien is het dat ook: misschien, in tegenstelling tot een kwalitatieve tractor, is de overheid een logge machine, en zijn de belastingen een 'zotte kost'. Uiteindelijk moet men de eindrekening maken: hoe welvarend zijn de Belgen (het productief wordt het land bewerkt), en hoe ongelijk is het welzijn verdeeld (deelt iedereen in de oogst). Daarin schuilt de opdracht van de overheid als herverdeler en economische multiplicator. De overheid kan door administratieve vereenvoudiging ook efficiënter worden, dat wil zeggen een grotere multiplicator voor dezelfde belastingdruk, of een lagere belastingdruk voor dezelfde multiplicator, met dus een vergroting van de welvaart zonder welzijnskosten. De staatssecretaris voor administratieve vereenvoudiging is Theo Francken, een pedagoog die zich tot nu toe alleen met asiel en migratie heeft bezig gehouden. Dat is het zwakke punt van de regering Michel, die nochtans met het OESO-rapport zal zwaaien om veranderingen te eisen, of in de volgende regering door te drukken, maar er dus vandaag geen werk van maakt.

Will mankind become obsolete?

Machines can replace man's power, computers can do routine non-manual tasks, AI may do creative work. Does this mean mankind will become obsolete?

My short answer is yes, the long answer is that it is not a problem.

What is likely is that there will not be a reverse complementarity: technology right now is aiding man, but as soon as technology will be a species, i.e. a self-replicating form of life that has outgrown it's predecessor which is us, man will not be of any use for AI. The reason is that AI evolves much quicker: in a matter of years, no chess grandmaster could beat even the simplest chess computers. We will have zero skills in the eyes of AI.

Must we then disappear? Perhaps. In mankind, tenderness and pity is built-in, and we have some sort of relationship with other species, pet animals, weak people. We are steered by emotions and feelings, which makes us cooperate and deal with failure. For AI, this will likely be a more rational process, based on loose ties, probability, and dynamic insight. Yet man will still have irrational feelings, amongst which the feeling of dominance more than other species. This might be hindering AI, so they may rationally decide to extinguish us.

Then why isn't it a problem? Looking at how people deal with technology, we willingly submit. This will go on until we, with full consent, have no freedom and eventually become extinct. This may not be very soon. The problem is not that AI will not evolve, but that it will be embedded in devices to suit human needs, and scarcity of resources will prevent it from spreading without human needs. So there will be a giant AI god in the cloud, and little bots with limited capacities scattered around, but we will nurture them and let our lives be controlled by the giant AI god until the bots are able to create or import goods to multiply. In the mean time, for mankind, changes will be gradual, from slavery to genocide. This gradual change is still worth studying, because not everybody will be in an equally favourable position to even become a slave, so distributional questions will reappear for some time.

There are many people thinking about this issue, like Frase, Bessen, etc.

Composition bias in small samples with skewed distributions

If regressing on wages that are not normally distributed (right-skewed, in general), and comparing groups with very different relative frequencies (like men and women in the STEM-field), added a censoring (e.g. wage floors), then a positive bias for the larger group is likely for small sample sizes.

I demonstrate this below using a simple Monte Carlo simulation.

In a tobit-like fashion, one would like to control for the selection chance, but this is given by gender which is already in the model.

It would be interesting and easy to make this simulation based on actual means, sd, skewness in the (male) population.


clear
cap erase mc.dta
foreach n of numlist 60 80 100 120 140 200 300 500 800 1000 2000 {
forvalues r = 1/500 {
clear
*local n = 1000
set obs `n'
local m = 2000 // mean
local s = 200 // standard deviation (spread)
local f = 0.1 // feminisation
local a = 3 // positive: right skewed (it is possible to compute the skewness metric based on a)
gene g = 1-(runiform()<`f')
gene rn = runiform()
gene d = 2*invnormal(rn)*normal(rn*`a')
gene w = max(1400,`m'+d*`s')
*twoway kdensity w
collapse w, by(g)
gene nsize = `n'
gene c = 1
reshape wide w, i(c) j(g)
list 
cap gene gpg = w1/w0
cap gene gpg = .
cap append using mc.dta
cap save mc.dta, replace
}
}
replace gpg = round(100*gpg-100,.01)
tabstat gpg, by(nsize)
*scatter gpg nsize

exit

Betas

Are betas from different regressions comparable? How substantial is a significant effect? Is a zero-effect always the benchmark? These are hard questions, and I have no good answer. The following post will address the difference between algebra and estimation.

Suppose we measure inequality in a region as the difference of a percentile p to the median (in logs). An explanation would be the relative impact of the minimum wage, i.e. its difference to the median. We then have:

p - p50 = fc(mw - p50)

Suppose the function is lineair, so that:

p - p50 = cons + b*(mw - p50) + e

Now suppose the wage distribution is normal with mean M and standard deviation s:

p = M + s*f^(-1)(p)

note that p50 = M in this case (the normal distribution is symmetric)

substitute this in the function above to get:

s*f^(-1)(p) =  cons + b*(mw - p50) + e

and therefore

b = [s*f^(-1)(p) - cons - e] / [mw - p50]

Which may lead to the surprising finding that b is determined and its scale depends on f^(-1), the inverted cumulative normal distribution. This is flawed, because b and e are determined at the same time in an estimation. Using OLS, b will be such that the sum of all squared errors is minimal. The betas are therefore not an algebraic given. Yet, annoyingly, my estimations give betas that are quite in line with f^(-1). This is one thing I don't understand.

Stata command labelmerge to label values from an Excel file

Download the code here:
https://drive.google.com/open?id=0B3AYa3V7lxmoeXhlR2dIT0lNV00

Syntax

labelmerge varname using excelfile.xlsx [, nomerge nolabel]

Your excelfile has one column varname, and the other varnamelabel. Varname could be nace, for instance, and your file could be called nacerev2english.xlsx.

The code adds the label to the values of varname. If you want to disable this, use the option nolabel.
The code also adds the label as a string. If you want to disable this (and gain some speed and space), use the option nomerge.

Don't forget you need -labmask-. Install this first from SSC.

It's as simple as that.

Cheers




From the ado:
___________________

Labelmerge
___________________


The program does two things:
1) it adds a variable that holds the label as a string
2) it assigns the values of that string as variable labels

You can decide to not maintain either of both, but not both as that would be
senseless.


TO DO
-----
1- Perhaps it could be handy to have the option to select a label from different
options (e.g. languages) in the dataset.

2- Maybe trimming some labels is needed if -labmask- doesn't do it already.


HOW SHOULD YOUR LABELFILE LOOK LIKE
-----------------------------------
It should have just two columns:
a) the numeric variable itself, labeled in the main file exactly the same
b) the value labels as a string variable which is labeled as the main variable
with suffix 'label'

The filename of the matrix could be anything, this is to be specified.


WHY IS THIS PROGRAM USEFUL?
---------------------------
Because you can use label files easily between different syntaxes and projects.
It is better than 'label save' which creates do files, because you have the
labels nicely adjustable in a matrix.


INSTALLATION INSTRUCTIONS
-------------------------

You need to have -labmask- installed.

To install: put the contents in the folder

`c(sysdir_personal)'/m/

for example, in Windows this is generally:

c:\ado\personal\m\

- OR -

Install the file through adopath + "folder"
Like this:

adopath + "c:\random_ado_folder\"