Algoritme voor een longitudinale, representatieve steekproef

Nemen we twee types steekproeven:

• Longitudinaal: steekproef in jaar t, eenheden opgevolgd door de tijd
• Cross-sectioneel: steekproef in jaar t, steekproef in jaar t+1, t+2, ...

Men zou denken dat deze benaderingen onverzoenbaar zijn. Nochtans is er een algoritme dat toelaat steeds representatief te blijven, én over longitudinale gegevens te beschikken.

Dit voorbeeld kan toegepast worden op de selectie van werknemers, waar de populatie afhankelijk is van de werkloosheid.

Jaar t

Men neemt een steekproef, bijvoorbeeld 25% van de populatie.

Jaar t+1

Er is uitstroom uit de populatie. Dit is geen probleem: aangezien de steekproef aselect is verwachten we dat de sample een gelijke uitstroom heeft. We behouden eenvoudigweg de cases uit jaar t.

Er is ook instroom. Hieruit moeten we opnieuw 25% gaan selecteren.

Jaar t+2

Uitstroom en instroom zullen zich telkens herhalen zoals in jaar t+1.

Er is ook herinstroom in de populatie. Dit betekent voor onze steekproef dat we alle ooit geselecteerde eenheden moeten opvolgen, en opnieuw opnemen als ze terug in de populatie komen. Zij blijven namelijk altijd 25% van het gelijkaardig segment (de herinstroom) vertegenwoordigen. De steekproef blijft dus representatief.

Coding sectors based on NACE rev 1.1 and NACE rev. 2

Below is a broad categorisation of the NACE activities in four groups:

1. Primary sector and construction
2. Manufacturing and energy (including water, waste and recycling)
3. Services and entertainment
4. Public sector, education and health (including libraries)

The syntax below can be used in Stata straight away:

Based on NACE rev. 1.1

gene s_industryR1 = .
replace s_industryR1 = 1 if y10_nace_rev1 >= 1 & y10_nace_rev1 <= 14 // primary sector + construction
replace s_industryR1 = 1 if y10_nace_rev1 == 45 // primary sector + construction
replace s_industryR1 = 2 if y10_nace_rev1 >= 15 & y10_nace_rev1 <= 41 // manufacturing + energy ressources
replace s_industryR1 = 2 if y10_nace_rev1 == 90 // manufacturing + energy ressources
replace s_industryR1 = 3 if y10_nace_rev1 >= 50 & y10_nace_rev1 <= 74 // services + entertainment
replace s_industryR1 = 3 if y10_nace_rev1 >= 91 & y10_nace_rev1 <= 97 // services + entertainment
replace s_industryR1 = 4 if y10_nace_rev1 >= 75 & y10_nace_rev1 <= 85 // PEH
replace s_industryR1 = 4 if y10_nace_rev1 == 99 // PEH

Based on NACE rev. 2

gene s_industryR2 = .
replace s_industryR2 = 1 if y10_nace_rev2 >= 1 & y10_nace_rev2 <= 9 // primary sector + construction
replace s_industryR2 = 1 if y10_nace_rev2 >= 41 & y10_nace_rev2 <= 43 // primary sector + construction
replace s_industryR2 = 2 if y10_nace_rev2 >= 10 & y10_nace_rev2 <= 39 // manufacturing + energy ressources
replace s_industryR2 = 3 if y10_nace_rev2 >= 45 & y10_nace_rev2 <= 82 // services + entertainment
replace s_industryR2 = 3 if y10_nace_rev2 >= 92 & y10_nace_rev2 <= 98 // services + entertainment
replace s_industryR2 = 3 if y10_nace_rev2 == 90 // services + entertainment
replace s_industryR2 = 4 if y10_nace_rev2 >= 84 & y10_nace_rev2 <= 88 // PEH
replace s_industryR2 = 4 if y10_nace_rev2 == 91 // PEH
replace s_industryR2 = 4 if y10_nace_rev2 == 99 // PEH

Info on the box: http://www.quackit.com/html/codes/horizontal_scroll.cfm

Global Labour Column (ILO)

Short, insightful articles on work. Well worth reading!

http://column.global-labour-university.org/

European Federation of Employee Share Ownership (EFES)

http://www.efesonline.org/

Doesn't have a lot to do with stats, besides the fact that it is quite an interesting subject. Typically, socialist trade unions oppose to the idea of employee ownership, which however contradicts the standard Marxist claim of employees ruling the factories. Strange fellows.

Stata: various

Below is a selection of practical stuff not worth spending a full post about

Display lead values

Some administrative sources or classification codes use fixed length numbers, which have leading zero's for the first so many numbers. To allow for this in Stata (effectively converting the number into a string), walk through the following page:

http://www.stata.com/support/faqs/data-management/putting-leading-zeros-in-output/

Polarization: TINA?

One big question that runs through my research is the contraposition of wage inequality and wage equality. At first, it seems like a very simple, nearly trivial point. Let me expand on it.

We all know that wages, by employer's request, have the tendency to move towards marginal productivity. However difficult to calculate, the difference between a brilliant order of one engineer and a stupid order of another one is more important than between a brilliant operation of one manual worker and a stupid operation of another worker. Hence, the good engineer gets paid a lot. This is in accordance with the demand for bright people in management, while manual workers have a whole army of unemployed equally unschooled workers that cause a surplus offer. Therefore, for each segment in the workforce, there is an optimal wage.

Ever since 2006, however, the world has discovered externalities. Externalities come in between seemingly Pareto efficient deals, such as the one discribed above. Would it be possible that two segments in the workforce are both better off if government intervenes? Wilkinson & Pickett believe so: inequality has a price. That price is to be paid by all, also by the rich. In so far that the underclass or precariat causes trouble, this price goes up. This is no moral position at all, I confess, but it may be a very convincing one. The upper segments will profit from having a lower wage, if it smoothens differences in society. Of course, the underclass gets leveled up, which may equally improve happiness and even provide chances for development. In the end, there will be a Pareto efficient equilibrium in some degree of wage inequality way less than the one based on marginal productivity.

Now there is a paradoxical complication in this reasoning: what is the optimal choice when the underclass causes trouble. One can suppress the consequences or the causes, and be indifferent between both options. For example, the upper class can demand a higher wage to compensate for increasing insecurity and the need to have private surveillance. This will actually be the first idea from a free riding micro perspective. It will fail for two reasons:
- The need to be surrounded by guards implies the cost of individual freedom in all cases. In a way, one could however still say that one can be bribed to accept this cost.
- Wages rise far above marginal productivity, which should be compensated by wages far below marginal productivity for lower skilled workers. This will however create ever more trouble, so that this solution is not stable.

In my view, therefore, there is a rational foundation for more equality, which may be the subject of specification in further research. I hope social sciences one day will be able to bring one and one together on this matter.

Latin abbreviations

APA has provided this list, where you'll find that a.o.:

• E.g. = exempli gratia = for example
• I.e. = id est = that is
• Cf. = confer = compare with
• Etc. = et cetera = and so on
• Well... et cetera.

Moreover, we should use al of these abbreviation only within parentheses (and footnotes maybe). Except for et al. (et alii), which is used all over the place. And mind you, when you use these abbreviations, there is no need to italicize!

Some more words of warning from the gentle folks at Sussex. Not.
And from Europe! Here.