Rediseño de Pauta de Observación de clases

To provide the context for results for the counterfactual analysis I first discuss changes in transition rates. As I am interested in long-run changes in worker tran- sitions, I focus on period transition rates. To examine changes in average transition rates I estimate a linear probability model for the probability to exit each state to a particular destination. Specifically, at the worker-level I regress transition dummies – taking on value 1 in year t for each worker in state A in year t who is in state B in yeart+ 1 – on period dummies for each of the seven periods. I thus run the following regression, separately for each destination and each demographic group:35

dA_itB = 7

X

j=1

δjpj_it+εit (2.5)

where dAB_it is the indicator variable for transitions from state A to B for workeri from the respective demographic group in yeart, pj_it is a dummy variable for period j= 1,2, ...,7, and εit is an error term. Estimates for δj give the mean

transition probability for period j, i.e. the period transition probability. For the ease of exposition, I display coefficients and confidence intervals at the 95 percent confidence level for each period in figures A.4 to A.13 in the appendix.

The aim of this analysis is to understand how changes in rates affect employ- ment share changes for different demographic groups. I therefore focus firstly on the change in transition rates over time, and secondly compare changes across groups, neglecting differences in levels for the most part. Also, as most coefficient estimates are significant, in the discussion I assume all estimates are significant unless other- wise stated. For the sake of brevity I focus on rates that prove to be important for interpreting counterfactual results.

Transition Rate Changes for Male Workers

The defining feature of job polarization is the disappearance of medium skilled jobs. A plausible proximate explanation for polarization is that workers reallocate from

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I exclude observations in years of discontinuities as well as the last sample year, as no flows can be discerned. The sample for non-employment outflow rates starts in 1976 as, due to the sampling scheme, no non-employed workers are observed for the first year. As linear probability models are known to suffer from heteroskedasticity, I use robust standard errors. Note that I do not include a constant.

medium skilled jobs to other types of employment. I therefore start discussing transitions out of medium skilled employment, shown in figure A.5.

If polarization reflects reallocation from medium skilled to other jobs, one would expect transition rates from medium to low or high skilled jobs to increase over time. This is not confirmed by transition rates: no general increase in the probability to reallocate from medium to low or high skilled jobs can be discerned. While these transition rates are very small from the start of the sample period, the probability to leave medium skilled jobs to other types of employment decreases for all age groups in period 3, although this partly reverses in more recent periods. In the most recent period, young male workers are much more likely to reallocate to a low skilled job, while for prime aged and older workers transition rates to high skilled jobs increase significantly. This conforms with decomposition results, finding that young male workers shift primarily to low, and prime aged and older workers to high skilled jobs. In recent years the shift away from medium to either low or high skilled jobs may reflect direct reallocation out of medium skilled employment. Does job polarization reflect a diminishing reallocation towards medium skilled jobs? Panel (b) in figures A.4 and A.6 shows transition rates from low and high to medium skilled jobs. For all rates there is a marked drop from period 1 to pe- riod 3, and rates remain low throughout the sample period. Reallocation from other job types into medium skilled jobs indeed declines. This implies both a decrease in upgrading for workers in low skilled jobs as well as a decrease in downgrading for high skilled workers.

Apart from reallocation between job types, polarization may also reflect an increase in the non-employment inflow rate, suggestive of an increase in job destruc- tion. Panel (d) in figure A.5 shows the corresponding transition rates. There is at best mixed evidence to support this claim. Workers are not generally more likely to move from medium skilled jobs to non-employment. In period 3 the probability to enter non-employment out of a medium skilled job decreases for all age groups. Prime aged workers experience a partial reversal of this decline in subsequent pe- riods, while young workers do exhibit a higher non-employment inflow rate from medium skilled jobs over time.

While the non-employment inflow rate is suggestive of job destruction, the non-employment outflow rate is generally associated with job creation. Changes in the transition rate from non-employment to medium skilled jobs, shown in panel (b) of figure A.7, provide evidence that job polarization may indeed reflect a decline in the creation of medium skilled jobs. Outflow rates from non-employment decline sharply after period 1, and generally remain low throughout the sample period.

Compatible with decomposition findings of a growing shift of younger workers to low skilled employment, we observe that young male workers are more likely to avoid non-employment by working in a low skilled job in recent years. This suggests that part of the recent rise in low skilled employment may reflect young workers reallocating to low skilled jobs from non-employment. The question arises whether this reflects a change in the worker’s employment type. Are young workers generally more likely to work in low skilled jobs, and to return to the same job type after non- employment, or are they more likely to return to low skilled jobs after entering non-employment from either medium or high skilled jobs?

Two caveats apply to transition rates into and out of non-employment. First, recall that non-employment is mismeasured, and can reflect migration or self-employment. Changes in non-employment inflow or outflow rates can therefore reflect changes in the probability to emigrate or become self-employed, or to return from either to PAYE registered employment in the UK, rather than changes in the probability to enter or exit non-employment.

The second caveat only applies to non-employment outflow rates: the sam- pling scheme suggests that part of the initial decline may reflect compositional changes in the stock of non-employed workers. Composition changes can reflect two factors: first, workers exhibit heterogeneous exit probabilities. Second, the exit probability of workers exhibits duration dependence. Either case implies the share of workers with high exit probability declines at the sample start, as the stock of non-employed workers in early years mostly contains workers who just entered non- employment.36 _{This implies a drop in the average exit probability. Using period 1} transition rates from non-employment as baseline rates for the counterfactual anal- ysis may therefore overstate the decline and so the contribution of non-employment outflow rates. To alleviate this concern, I additionally use transition rates which have been corrected for compositional changes when conducting the counterfactual analysis. Corrected transition rates confirm that non-employment outflow rates to

36_{Note that hazard rates estimated in chapter 3 show that the exit probability generally decreases}

with non-employment duration, which suggests either worker heterogeneity or duration dependence are present in the sample.

medium skilled jobs decline after period 1, although the decline is smaller.3738 Finally, I consider transition rates from sample entry. Transition rate changes are shown in figure A.8.39 _{Entry rates for young workers generally reflect the first} time workers enter the labour market. Prime aged and older workers primarily enter the sub-sample because of aging, so their entry rates largely reflect propensities prior to sample entry.40 For young workers the figure reveals a dramatic rise in the probability to enter the labour market in a low skilled job and a matching decrease in the probability to enter in a medium skilled one. While young workers at the start of the sample period predominantly begin their career in a medium skilled job, and only rarely in a low skilled one, entries in low and medium skilled jobs are almost equally likely by the end of the sample period. Interestingly, entry into high skilled jobs also decreases by a substantial amount. This suggests that part of the large shift of young male workers towards low skilled jobs results from workers directly entering into low skilled jobs. The fact that older age groups exhibit less pronounced distributional shifts towards low skilled jobs may be taken to imply that workers eventually reallocate from low to other job types.

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Worker heterogeneity and duration dependence both imply that workers with longer durations exhibit a lower exit probability. I therefore compute corrected transition rates for period 1 as a weighted average of duration-specific exit probabilities, using weights observed in period 3. The remaining decline in outflow rates from period 1 to period 3 is entirely driven by decreasing duration- specific exit rates, which are independent of worker heterogeneity and duration-dependence. As the decline abstracts from compositional changes, I take the contribution of correct transition rates as a lower bound. Corrected transition rates suggest exit probabilities in period 1 to medium skilled jobs of 0.1908 (young workers), 0.1543 (prime aged workers), and 0.0881 (old workers) respectively. For exits to low and high skilled employment respectively, these change to 0.0230 and 0.0344 (young workers), 0.0162 and 0.0376 (prime aged workers) and 0.0122 and 0.151 (older workers).

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Note that findings in chapter 3 support a decline in non-employment outflow rates indepen- dently of these issues: estimating hazard rates for male workers entering non-employment in each period shows that workers entering in later periods generally experience longer spells. Longer non- employment durations are consistent with a decline in the non-employment outflow rate. Chapter 3 also shows that longer non-employment durations are driven by a decline in the outflow rate to medium skilled jobs. Results are also roughly in line with changes in non-employment outflow rates for women.

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Note that sample entry to non-employment for young workers reflects workers who enter NESPD or ASHE before the age of 18. These workers enter my sample at age 18 in accordance with my definition of the working population as comprising workers aged 18 to 65 years.

40_{Entry rates for prime aged and older workers in period 1 are the exception: NESPD began in}

1975 by sampling PAYE registered employees, entry into non-employment is therefore very low for prime aged and older workers compared to later periods. As one can see in panel (d) of figure A.8, entry rates to non-employment rise very sharply from period 1 to period 3. Because entry rates to all states sum to one, this affects all entry rates for period 1. However, this does not affect results for the counterfactual analysis as I use entry rates from period 3 as baseline rates for these workers.

Transition Rate Changes for Female Workers

Patterns for transition rate changes for women are similar to those for men. Here I discuss only notable differences in transition rates which are important for the counterfactual analysis. Transition rates for women are shown in the appendix in figures A.9 to A.13.

Focusing first on transitions out of medium skilled employment, as for men there is no general tendency to leave medium skilled jobs for low or high skilled ones. Only in recent years do women become more likely to directly reallocate to other job types. Recall that one explanation for the decline in medium skilled jobs is an increase in job destruction. There is no evidence for men that job destruction is driving the decline in medium skilled jobs. For women, there is even evidence to the contrary. The probability to enter non-employment from a medium skilled job declines for all age groups.

Transitions out of non-employment also exhibit a very similar pattern to men, with exit rates from non-employment declining from period 1 to period 3 and remaining largely flat thereafter. One exception applies to young male workers. As seen above, they exhibit a fairly steep increase in the probability to leave for a low skilled job in recent years. This also applies to young women, who, additionally, also see a comparatively large increase in their probability to leave to high skilled jobs. Recall that young women, in contrast to young men, do not shift away from high skilled jobs. Note that I display uncorrected transition rates for period 1 here. Using corrected rates non-employment exit rates are generally lower, but still exhibit a decline from period 1 to period 3 for prime aged and older women.41