Friday, March 10, 2017

Following the substantial uptick in manufacturing output fuelled by sterling's depreciation at the end of last year, the January data indicate a month-on-month fall of some 0.9%. This has contributed to a month-on-month fall of 0.4% in total industrial output. Year-on-year, industrial output still shows a large rises, of some 3.2%.

The slowing of output in January leads to another major revision in my neural network forecast for this variable over the coming 24 months - illustrating again that forecasting in such volatile times is a hazardous activity. The latest forecast is shown below - and is clearly more consistent with forecasts produced over the course of most of last year than with the one produced last month.

Friday, February 10, 2017

The latest statistics on industrial production indicate that, compared with a year earlier, output in the production sector in December 2016 had grown by some 1.2%. This spurt of growth is new. Indeed, industrial output grew by over 3.1% over the last 2 months of 2016, following some earlier reverses. The main driver of this growth is in the manufacturing sector, which, over the course of the year, increased output by some 4 per cent. Growth in manufacturing since October has been particularly strong - at 3.5 per cent over the two months alone.

Using these data to update my neural network forecaster for industrial output means that - with the positive annual growth rates recorded in each of November and December of last year - the forecast is now for continued growth over the period to the end of 2018. The depreciation of sterling has clearly given manufacturing exports a boost, and while the series dipped in October of last year this dip has proved to be much milder and shorter-lived than anticipated. The uncertainties brought on by Brexit have clearly made forecasting an even more hazardous activity than usual!

Friday, January 06, 2017

Comments by Andy Haldane, chief economist at the Bank of England, comparing economic forecasts to the famous failure of Michael Fish to predict the October 1987 hurricane have been seized upon by the media. The relevant part of Haldane's commentary comes in the 5 minutes from 15m30s in this video.

A number of points are worth making about this. First, the specific forecasting failure that Haldane compares to Fish is that of the financial crash leading to the Great Recession. Some media outlets have suggested otherwise. Haldane does comment on the Bank's forecasts for the post-referendum period and notes that the economy has been more resilient so far than had been expected, but he continues to expect a relatively tough year in 2017.

Focusing then on the major forecasting failure in 2008, he identifies two contributory factors. The first (extending the analogy with meteorology) is a lack of data. With better data, better forecasts can be produced. The second is arguably more fundamental. As Haldane notes, the forecasting models tend to work well when the economy is close to equilibrium, but perform badly during the (more interesting) periods following a shock. They clearly need to be redesigned, and indeed are being redesigned, better to accommodate such extreme events. Much effort since the crisis has gone into developing macroeconomic models to include imperfectly operating housing markets, and it is likely that this effort will contribute to more successful forecasting in future.

That said, economies are made up of people with free wills, and forecasting in this context can never become an exact science. The forecaster's tools - be they VAR models, neural networks, DSGE models or whatever - allow the evidence to be marshalled systematically in order to produce informed estimates of the likely time paths of key economic variables. But they are informed only by what is known at the time of the forecast, not magically informed by data that are unavailable. That said, data on the vulnerability of the sub-prime sector were available in 2007, and it is certainly fair to say that these should have been given greater heed in forecasts.

However, while many laypeople consider forecasting to be a major part of what economics is all about, that perception is misleading. Most economics is based on generating hypotheses that are then tested on historical data. This allows some stylised facts to be determined, and helps us understand a complex world - for instance: production quotas raise the price of oil; or restricting trade is harmful to growth. The body of economic understanding that has developed in this way over many years is in no way challenged by the fact that (in common with everybody else) economists lack perfect crystal balls.

Wednesday, December 07, 2016

Industrial production in October of this year fell some 1.3% over the month and 1.2% over the year. My neural network forecaster suggests that this heralds the start of a downturn in industrial output that has been foreseen for some time - but that has been delayed by the depreciation of sterling. Forecasting a series of this kind in the current climate, given the considerable uncertainties surrounding Brexit terms and the consequent impact on trade, is of course very hazardous. But, even without these considerations, the climate for the production industries has not been particularly propitious.

This being so, the government's proposals for an industrial policy are, in principle, welcome. This should not be a policy about picking winners (on which governments have a poor track record), but about providing a climate wherein winners can thrive. One key component of such a policy should surely be openness to trade.

Friday, December 02, 2016

The government's approach to Brexit negotiation has been rather difficult to fathom - partly because the undertaking not to give a 'running commentary' has made pregnant every least significant ministerial utterance. But, insofar as one can make sense of the government's position at this stage, it is this: the government wishes to negotiate a relationship with the EU that is outside the EU and outside the EEA, but which is at least as advantageous to the UK as EEA membership would be. Specifically, it is looking to remove the UK from the plethora of regulations that essentially define the EEA - the non-tariff barriers that define standards for goods and services - and wants to replace this with a system of mutual regognition (MR). So, instead of accepting a single set of European standards, the UK would be allowed to define its own standards, but trade between the EU and UK would remain unhindered because each of the UK and EU would accept the other's standards. At the same time, being outside the EU and the EEA might unambiguously allow the UK to impose restrictions on the movement of labour. This adoption of MR might be what 'sovereignty' looks like.

For both sides to the negotiation to accept MR would require it to be understood that there are limits to the extent to which standards can diverge. The EU is unlikely to accept MR as a principle without restricting the UK's ability to define standards that, in effect, produce serious non-tariff barriers - and the same goes the other way. Sovereignty is diluted by this. Moreover, the definition of a whole bunch of new standards for the UK implies the creation of a huge bureaucracy. 'Leave' voters who were concerned by the Eurocracy would not likely be impressed. And both the UK and the EU will have red line conditions attached to any MR agreement - it is unlikely that the UK would manage to secure an agreement of this kind without both continued payments to the EU and conditions being met on the mobility of labour.

If this is indeed the way the government is thinking, it is not the worst of all possible worlds. But, once it has been negotiated through, the merits of such a proposal, relative to those of simply remaining within the EEA, are not at all clear.

Tuesday, November 08, 2016

The latest data on industrial production show a year on year rise of some 0.3%, but a month-on-month fall of 0.4%. The quarterly data show a fall of some 0.5% in the third quarter of this year - the first complete quarter since the Brexit referendum. While some parts of the economy have so far proved resilient to the outcome of that vote - stimulated by the cheaper pound - other sectors are clearly already struggling. In particular, manufacturing output has fallen over the quarter by some 0.9%.

Using my neural network forecaster to look ahead continues to suggest that this series is likely to dip over the medium term. Forecasting is always a hazardous activity, but at no time more so than this, given the uncertainties that remain over how Brexit is to be implemented.

Friday, October 28, 2016

The employment tribunal ruling that Uber drivers are employees rather than being self-employed sub-contractors has major implications for the development of the labour market. Much evidence suggests that there has been a large growth of employment in the-so-called 'gig economy', where a firm puts workers in direct contact with clients to undertake specific one-off tasks (or 'gigs'). The firm acting as co-ordinator between workers and clients arranges the gig - and is often assisted by technology in doing this - and takes a commission for doing so. Hence, in the case of Uber, a passenger uses her digital device to arrange a journey, and Uber's software is used to find a possible driver. Till now, the drivers have been considered to be self-employed.

Working in the gig economy offers advantages and disadvantages. Work arrangements can be very flexible. But as self-employed workers, many of the protections available to employees have been absent. So, for example, gig economy workers cannot access sick pay unless they make insurance arrangements themselves - and there are moral hazard reasons why this might be difficult. Likewise they are likely to have to make their own pension arrangements. If they are available for work at a time when no work is offered, they may in effect be paid below the minimum wage. For some workers, involvement in the gig economy supplements a more regular job. For others, the main source of income is the gig economy. And for this latter group, the lack of job security can be a problem.

It is, however, a problem not only for the individual worker, but for the economy more generally. If workers do not have a long term engagement with an employer, they are likely to lack the structures that have conventionally accompanied a job - in particular training, development and progression. While some parts of the gig economy involve highly skilled work - freelance journalism, or business consultancy, for example - others less so - and here driving is a classic example. In the absence of a career structure, workers will lack the opportunity to develop to their full potential, and, for the economy as a whole, this creates a productivity gap. If the future of work is increasingly characterised by a looser set of ties between employers and employees, institutions other than the employer will be needed to provide the mechanisms that ensure development, progression and productivity enhancement. Membership organisations may be one way in which this role can be fulfilled. Unions are one example, accreditation bodies are another.

The finding of the employment tribunal will raise Uber's costs and this in turn will diminish its competitive advantage. If Uber can survive this, then its employees will benefit from the new employment security that they will enjoy. Otherwise, Uber may not be able to operate in the UK.

In this digital age, however, solutions similar to Uber, possibly operated from other legal jurisdictions, would be sure to emerge to fill the gap. While the tribunal ruling shifts the responsibility for employment security onto the employer in this case - and while many other gig economy businesses will need to consider the ruling carefully - a more comprehensive solution may be to look to other institutions than the employer to provide workers with security, development, progression and productivity enhancement.