Fact-checking a few claims about the NHS

What with the campaigning for the general election having gotten into full swing last week, many claims have been made regarding which Party would be better for which aspect of security, the economy, education etc. One particular video regarding the NHS started doing the rounds on Facebook a few days ago. This video makes a number of claims regarding the supposed impact that the recent Coalition and Conservative governments have had on the NHS, with the video then going on to suggest that a Conservative government would be bad for the NHS. For a bit of excitement, here is said video:

 

 

The claims made in that video are many. Some are valid, whereas others are not. Let’s take each of them in turn.

Claim 1: We are experiencing the largest sustained drop in NHS funding as a percentage of GDP since the NHS was founded.

Reality: This claim is false. As per the information shown in the graph below (from the Institute for Fiscal Studies) NHS spending as a proportion of GDP has been stable over the past couple of years, and the decrease between 2009 and 2012 was no larger or longer than decreases in the mid-to-late 1970s or mid-1990s.

bn201_fig1

Moreover, the more relevant metric of NHS spending per capita continues to increase – in other words, more is spent per person on the NHS than ever before, although the rate of that increase has slowed in recent years.

bn201_fig2

Claim 2: If the internal market was abolished we [i.e. the NHS] could save billions.

Reality: This claim is also false. The internal market actually creates savings and is not “wasteful” as is claimed in the video. On the contrary, it promotes competition and stimulates the NHS to provide better services – importantly, the benefits of competition in healthcare are well established. Furthermore, it is actually the refusal of many within the NHS to accept the proven benefits of competition that is causing some harm to the NHS – indeed one of NHS Improvement’s main aims is to promote and encourage “buy-in” of competition among those in the NHS. Hence, abolishing the internal market would actually cost billions rather than save them.

Claim 3: Health tourism costs the NHS £200 million per year, which is insignificant in terms of the overall cost of the NHS.

Reality: This is generally true – although the costs to the NHS associated with people who are not ordinarily resident in the UK are of the order of £2 billion per year, that includes many people who did not come to the UK specifically and solely to use the NHS (i.e. it includes people who are not “health tourists”. Instead, estimates put the upper bound of the costs associated with those who travel to the UK for the sole purpose of using the NHS at around £300 million per year. When compared to the total annual NHS budget of about £90 billion, the costs associated with health tourism are indeed a trivial amount.

Claim 4: Immigrants are not ruining the NHS, they’re running the NHS.

Reality: True. Immigrants from within the EU currently represent about 10% of doctors and 4% of nurses. If non-EU immigrants are included, therefore, the figures are likely to be slightly (although probably not a huge amount) higher. Given that there are already quite severe labour shortages within the NHS, it is clear that without the immigrants currently working within the NHS, the functioning of the NHS would be severely hampered. Moreover, immigrants are net contributors in terms of taxes vs benefits, so also contribute to the NHS in that way. Hence, the claim that immigrants are not ruining the NHS is clearly valid.

Claim 5: 1 in 10 nursing posts are vacant and the nursing bursary has been scrapped

Reality: True. The nursing bursary was indeed scrapped at the start of the year – this means that there is a much-reduced incentive for people to train to become nurses as they will now have to pay £9,000 in tuition fees per year in order to do so. This is likely to lead to problems recruiting sufficient nurses in future. Notwithstanding that, there are also problems recruiting nurses now – the Royal College of Nursing suggests that 1 in 9 nursing posts are now vacant. This figure is actually marginally worse than that claimed (11% vacancy rate vs the 10% claimed).

Claim 6: Tens of thousands of sick patients waited on A&E trolleys this past winter

Reality: Likely to be true. Using data from Quality Watch (and a bit of approximation / extrapolation), roughly 6 million people attended A&E last winter. Of these, around 15% were not seen within the government target of four hours – i.e. about 900,000 people waited more than four hours in A&E. Now, it seems unlikely that all of these people waited on trolleys specifically, but even if only 10% of these people (i.e. 1.5% of all admittances to A&E) did then the “tens of thousands” figure would be accurate. Hence, this claim seems plausible.

Conclusion: As with most of these election video type things, the video contains some claims that are true, some that are likely to be true, and some that are demonstrably false. Does this mean that the Conservatives are the worst Party for the NHS? Who knows?! That’s for you to decide and take into account (if you want to) when you vote. But at least when doing so, you’ll now have a more complete set of facts when you do.

 

Immigration benefits us all – now the IMF gets in on the act

Only a short time after the Foged & Peri paper (summarised here) found that an “influx” of immigrants to Denmark benefited the both high-skilled and low-skilled workers in the local population, the IMF has examined whether or not those results apply to other advanced economies.

And, guess what? They do! Unsurprisingly.

In order to do so, the study uses a fairly nifty approach to accounting for potential reverse causation between migration and GDP per capita (since migrants might prefer moving to countries with higher GDP per capita in the first place). The study uses a “gravity model” to instrument for the share of migrants in a country, including various “push” factors (such as growth in the origin country, demographic variables etc.) and other controls, proving once again that describing something as “gobbledygook” just because you don’t understand it isn’t a particularly sensible thing to do.

The paper’s main findings are threefold. First, a 1% point increase in the proportion of population made up by migrants actually increases GDP per capita by 2%. Interestingly, this benefit arises via an increase in labour productivity, rather than an increase in the proportion of the population that is of working age.

For example, high-skilled immigrants can increase productivity through innovation and positive spillovers on native wages, while low-skilled workers can increase productivity by enabling native workers to re-train and move into more complex occupations (exactly as was found by Foged & Peri). An alternative mechanism cited by the IMF study suggests that the presence of low-skilled female immigrants increases the provision of household and child-care service, thereby increasing the labour supply of high-skilled native women. This result is robust to controlling for technology, trade openness, demographics, and country development.

Second, these benefits arise from both low-skilled and high-skilled migrants. As above, both skill-types affect GDP per capita through increasing labour productivity, rather than via increasing the proportion of the population that is of working age. However, the effect does appear to be more statistically significant for migration by low-skilled workers than it is for high-skilled migrants.

The study suggests that this difference could reflect differences in the impact of high-skilled migrants across different countries, but this seems unlikely to be sufficient to render the impact insignificant. More likely is the second reason posited by the study – namely, that high-skilled migrants initially might have to obtain jobs for which they are over-qualified, thereby meaning that their impact on the incentives of high-skilled native workers to retrain etc. is limited at first.

Third, the benefits to native workers arise across the entire income distribution. Both low-skilled and high-skilled immigration increase the GDP per capita of those in the bottom 90% of the income distribution by roughly the same amount, while high-skilled immigration increases the GDP per capita of those in the top 10% of the income distribution by roughly twice as much as does low-skilled immigration.

However, the study does not really examine the distribution within the bottom 90% particularly closely – the study just looks at the estimated impact of immigration on the Gini coefficient to conclude that the distribution within the bottom 90% would not be changed significantly. The study should, instead, have looked at, say, the impact of immigration on each decile or quintile of the income distribution separately so as to give a more complete picture of the impact of immigration across the income distribution.

The paper (and particularly the blog post linked to above) ends by getting somewhat more political. In particular the study suggests that there is a need for improvement in terms of providing support for native workers that want to re-train, find a new job etc. However, these policy suggestions are made without taking into account the fact that some countries do already have plentiful such schemes in place, to the extent that increasing the provision of such schemes in those countries might not be efficient. Of course, that’s not to say that some countries would benefit from increasing the provision of such schemes.

Glassdoor’s “contribution” to gender wage gap research

In a whirlwind of publicity and self-promotion, Glassdoor recently released the results of a “study” that claimed to prove the existence of a gender pay gap even when potential differences in areas such as “personal characteristics, job title, company, industry and other factors” are accounted for. As a result, Glassdoor boldly claims that men are paid about 5% more than women.

However, the approach used by Glassdoor is subject to a major problem. In particular, Glassdoor’s approach relies on them being able fully to control for all other factors (such as experience, qualifications etc) that might determine someone’s wage. Although Glassdoor notes this themselves (in a single paragraph relegated to the back of their report), they do not qualify any of their headline results with an acknowledgement of this.

Seeing as Glassdoor only includes controls for a few personal characteristics (such as age, qualifications, and experience) and some factors relating to a person’s occupation and industry (such as job title and company name). In other words, Glassdoor excludes a number of relevant factors that are likely to be relevant when it comes to explaining someone’s wage.

Indeed, other studies have found that factors such as ethnicity, whether or not someone is a member of a trade uniona person’s mental and physical health, and even language skills can be important determinants of a person’s wage. The Glassdoor study does not account for any of these, and thereby erroneously attributes differences in wages that could be due to these (or other factors) to the gender pay gap.

In addition, the Glassdoor study does not seem to account for whether or not someone is working part-time or full-time – as part-time workers are likely to be paid less than full-time workers, even on an hourly basis, Glassdoor’s apparent failure to include such a distinction in their analysis could bias their results substantially. Similarly, the Glassdoor study does not even try to account for potential unobservable differences (such as personal preferences regarding careers), and this failure further biases Glassdoor’s estimate of the gender pay gap.

Finally, the data used by Glassdoor are from self-reported salaries and characteristics that are recorded by members of the Glassdoor website. There are plenty of reasons to suspect that these data are unreliable – at the very least, it is widely recognised that figures that are self-reported are likely to be subject to considerable bias, such that relying on them for a study such as this is nonsensical.

Therefore, it is clear that Glassdoor’s “study” into the gender wage gap is merely an exercise in self-promotion rather than a useful contribution to the substantial amount of past research that has been conducted on this issue.

Corbynomics and the expropriation of private assets

With Jeremy Corbyn’s victory in the Labour leadership elections, there likely will be a renewed focus on Corbyn’s economic policies.  Indeed, there has already been some interesting analysis of Corbyn’s proposal for “people’s QE” and the ramifications that would have for the (instrument) independence of the Bank of England (see Simon Wren-Lewis’ mainlymacro blog).

However, one area of Corbyn’s stated economic policy that has received less attention is his desire to (re-)nationalise the energy, rail, and banking industries. It is conceivable that there might be a re-hashing of the age-old debate regarding the relative advantages and disadvantages of privatisation vs nationalisation, with the same age-old conclusions.

Much more interesting, on the other hand, is the mechanism (and the implications of said mechanism) by which Corbyn proposes to carry out his re-nationalisation policies. Specifically, Corbyn has stated that he “reserves the right to” nationalise a firm “”with either no compensation or with any undervaluation deducted from any compensation for renationalisation.” (as reported by The Independent)

In other words, Corbyn has stated a potential desire to expropriate a privately-owned firm (or multiple firms) while providing a less-than-market return on the assets that a Corbyn government would acquire.This is likely to have a dramatic impact on private incentives to 1) acquire any of the assets that the current Conservative government would privatise over the next five years; 2) invest in the energy and rail industries that Corbyn has said he already wants to re-nationalise; and 3) invest in other industries in the UK.

First, Corbyn thus far seems to have restricted the target of this policy to firms that are privatised by the current Conservative government over the next five years.  Therefore, the heaviest impact is likely to fall on those assets that the current Conservative government was planning to sell off over the next five years. In particular, Corbyn’s expropriation policy is likely to reduce the amount of money any selling-off of assets by the current government is able to raise.

To see this, note that should a Corbyn Labour government win the 2020 election, any asset sold off by the current government between now and then would be taken back by the Corbyn Labour government. This means that any private entity thinking of purchasing any asset the current government sells off would need to factor in the possibility that they lose control of (and, hence, also lose any profits resulting from) that asset in 2020.  As such, a private entity would reduce the amount it was willing to pay for the asset being sold-off – the obvious result of this is that it reduces the amount of money the current government would be able to raise from selling-off any assets (with the associated implications concerning any reduction of the national debt).

It is possible that this makes selling-of the asset not to be worthwhile such that the current government decides to retain control of it after all (perhaps this is Corbyn’s plan all along?). If so, then it would mean that assets that might be put to more efficient use in the private sector instead continue to be run by the public sector (with the resulting potential impact on GDP).

Second, although Corbyn does seem to have restricted his expropriation policy to government assets that are sold off between now and 2020, there remains the possiblity that he extends that policy to his entire re-nationalisation aims.  In other words, Corbyn could conceivably expropriate the assets of energy and rail companies.  This introduces substantial uncertainty regarding the rate-of-return energy and rail companies can expect to obtain on any investments they might make between now and then. As increased uncertainty regarding the rate of return of an investment results in fewer investments being made (see here and here), the impact of Corbyn’s policy (even if Corbyn is not elected in 2020) is to reduce the current levels of investment made by firms in these industries. This comes at a time when both the energy and rail industries are in need of substantial investment in new infrastructure – anything that reduces the incentives of these firms to make these necessary investments cannot be a good thing.

Third (and this is somewhat speculative on my part), to the extent that Corbyn might wish to expand his nationalistion policy to other industries, the same impact would be felt in those industries.  However, the impact in these as-yet-unnamed industries may well be negligible, particularly in comparison to all the other areas of uncertainty that affect firms’ investment decisions (at least until any further nationalisation policies are stated).

It remains to be seen if Corbyn gets a chance to implement his policies, but, regardless those stated policies are already having an effect. Corbyn needs to clarify exactly what his plans regarding nationalisation are very soon lest those effects grow substantially.