Six years ago, I wrote a post The greying of Europe’s farmers which reviewed the evidence on the ageing of farm operators up to that point in time (the latest data available referred to 2007). The data confirmed that Europe’s farmers were getting older. However, I questioned whether this was evidence of a growing policy problem. Instead, I suggested “that what we observe is a slow upward shift in the age distribution which can be explained by general social trends (longer schooling periods and longer longevity) rather than any specific worsening of the generational transfer problem in agriculture as such.”
The greying of Europe’s farmers continues…
The recent publication by Eurostat of the first results from the 2016 Farm Structure Survey allows us to revisit this issue. The table below shows trends over the period since 2005. Because 2016 data are not yet available for four Member States (Belgium, Croatia, Italy and Luxembourg) I provide two series in the table – one for the EU-28, and the longer series for the EU-24.
Because Italy with its 1 million farms (around 9% of the EU total) has a relatively poor age structure, the figures for the EU-28 show a somewhat more unfavourable picture than for the EU-24. However, the trend in the two series is similar. There is a decline in the share of younger farmers (those under the age of 35) and an increase in the share of older farmers (those over 54 years of age).
Notes: Croatia not included in 2005 figures for EU28. Belgium, Croatia, Italy and Luxembourg not included in EU24 figures because of missing 2016 data.
Some readers may be familiar with the excellent report written for the European Parliament in 2017 by Lukas Zagata and his colleagues Young farmers – policy implementation after the 2013 CAP reform. These authors present a similar table for the EU28 with data to 2013 (their Table 1) but with a lower figure for the share of older farmers in 2013. This leads them to emphasise that “these proportions have not significantly changed over the last decade, varying by only a single percentage point” (bolding in the original). However, with the changed 2013 figure and the additional data point for 2016 for the EU24, the evidence is clearer that the ageing of farm operators continues.
…but with different experiences between Member States
An important point made in that European Parliament report is the heterogeneity of Member State experiences. The issue of generational renewal does not have the same salience across Europe.
In the figure below, I have divided Member States into four groups depending on how they compare to the EU average for (a) the share of younger farmers (X-axis) and (b) the share of older farmers (Y-axis). The four quadrants represent the four groups. I have used 2013 data for this figure because of the more complete coverage of EU Member States.
Typology of Member States with respect to age structure of farm operators, 2013
Source: Alan Matthews, own compilation based on Eurostat 2013 Farm Structure Survey
(click on image to enlarge)
The upper left-hand quadrant shows countries with an above-average share of older farmers and a below-average share of younger farmers; these are the countries where problems of generational renewal are most acute. These are mainly countries in southern Europe, although the UK is an unexpected member of this group.
Conversely, the lower right-hand quadrant shows countries with a much more favourable age structure; these countries have a lower share of older farmers and a higher share of younger farmers than the EU average. This group takes in mainly countries from central Europe, if that concept can be stretched to include Finland.
The lower left-hand quadrant contains three countries, all from north-west Europe. They are characterised by a lower share of younger farmers but also a lower share of older farmers.
Finally, the upper right-hand quadrant contains two eastern European countries Bulgaria and Hungary which have both higher shares of younger but also higher shares of older farmers.
The contrast, in particular, between Portugal and Cyprus, on the one hand, and Austria and Poland, on the other hand, highlights the importance of national factors in influencing generational change in agriculture. These include differences in farm structure (countries with smaller farm sizes tend to have older farmers), differences in national legislation on inheritance, fiscal policy and retirement schemes, as well as social and cultural attitudes around farm succession.
Analysis using the Labour Force Survey
The Farm Structure Survey data on the age structure of farm operators confirms that the ‘greying’ of farmers continues. But does this suggest that the issue of generational renewal in agriculture has become more serious over time? Does it strengthen the case for policy intervention?
In fact, there is good evidence that this issue reflects a wider social phenomenon, linked to demographic change in Europe, the fact that younger people are staying longer in education and thus delaying their entry into the workforce, and that increases in life expectancy have encouraged workers to delay their retirement. Simply put, older people remain active for longer.
On average, life expectancy at birth in Europe has increased by one year in each recent five-year period (it increased from 77.7 years to 80.6 years over the past 15 years, although data for 2015, the latest year available, show that there was a decline in Europeans’ life expectancy for the first time since 2002 in that year).
To add perspective to the Farm Structure Survey (FSS) data, age structure data from the Eurostat Labour Force Survey (LFS) data can be examined. This has the great merit of allowing a comparison of trends in the agricultural labour force and in the workforce at large. Because demographic changes take place slowly over time, I have confined the data analysis to the EU-15 to allow a comparison over the longer period 1995 to 2016 (excluding Luxembourg due to missing data for some years).
The field of survey of agricultural employment in the LFS is different to the FSS. The FSS is a survey of operators of agricultural holdings, regardless whether they are full-time or part-time. The LFS assigns people to an industry based on their principal source of employment. Thus, a veterinary surgeon who happens to own a farm would be included in the FSS but not in the LFS definition of agricultural employment. On the other hand, the FSS is a survey of farmers only, while the LFS also includes those whose principal employment is in agriculture regardless whether they are a farmer, a relative assisting or a salaried worker.
The first chart below compares the changes in young workers in agriculture compared to the total economy (to be strictly accurate, the comparison should be with the non-agricultural economy, but as the share of agricultural employment in the total labour force is relatively minor (under 5%) in the EU-15, I have taken this shortcut). For each country and the EU-15, the first two bars show the change in the share of younger workers in the overall labour force. The second pair of bars shows the same change for agriculture. The key message: a declining share of younger workers is not unique to agriculture, but reflects a general trend in the workforce.
Source: Own calculations based on Eurostat database lfsa_egan2 (for total employment) and lfsa_egan22d (data for crop and animal production, hunting and related service activities).
(click on image to enlarge)
In fact, we can draw a stronger conclusion. For the EU-15 as a whole, the share of workers in the 15-39 age group fell from 53.6% in 1995 to 41.7% in 2016, a drop of 11.9 percentage points. The share of workers in this age group in agriculture fell from 38.0% in 1995 to 30.2% in 2016, a drop of 7.8 percentage points. In other words, the entire fall in the share of younger workers in agriculture can be explained by general social phenomena affecting all workers. We do not need to look for explanations which posit that there are some unique problems specific to agriculture.
The next graph looks at the shares of older workers in agriculture and the overall labour force, respectively. The increase in the share of older workers (55 years and over) particularly in the total labour force has been quite staggering. The share of older workers in the total labour force in the EU-15 has increased from 11.2% to 29.0%, an increase of 18.4 percentage points. For Greece and Portugal, the figures are even more striking. For Greece, the increase is from 17.6% to 42.7%, or 25.1 percentage points. For Portugal, the increase is from 16.8% to 52.3%, or an increase of 35.5 percentage points.
The share of older workers in the agricultural labour force has also increased, but not to the same extent. For the EU-15, the share increased from 18.8% to 32.0%, or an increase of 13.2 percentage points. As the increase in the share of older workers in the total labour force was 18.4 percentage points, this again shows that the ageing process in agriculture by and large reflects broader social phenomena. In fact, the share of older workers in the total labour force in 2016 (29.6%) is now very close to the share in agriculture (32.0%). The idea that agriculture is somehow exceptional in the changes in its age distribution simply does not stand up.
Source: Own calculations based on Eurostat database lfsa_egan2 (for total employment) and lfsa_egan22d (data for crop and animal production, hunting and related service activities).
(click on image to enlarge)
LFS vs FSS data – do the stories differ?
The sharp-eyed among you will note that the percentage shares shown in the previous two charts for younger and older workers in agriculture, respectively, derived from LFS data, differ quite markedly from those shown in the first table in the post, drawn from FSS data. The FSS data support the oft-quoted statistic that more than half of farm operators are 55 or over. The LFS data suggest that the proportion is closer to one-third. Similarly, almost one-third (30%) of workers are in the younger age groups in the LFS data, while the FSS data show a figure of just over 5%.
There are various ways in which these two sets of figures might be reconciled. Most obviously, the age bands for the younger farmers are different (less than 35 for the FSS and less than 40 for the LFS). Adding the extra 5-year cohort from 35 to 39 years of age to the younger group will obviously raise its percentage share.
For the older age group, there might be a greater tendency for older farmers to declare their principal occupation as retired rather than farmer, which might account for some of the discrepancy in the percentage shares.
Importantly, the coverage of the LFS includes family and salaried workers. Family workers may be sons or daughters working on the farm as potential successors who, by definition, would be younger than the farm operator. This could be another reason why the LFS data shows a less skewed age distribution than the FSS data.
This last is an important point, as it highlights a potential problem in relying on the FSS data to describe the age structure in agriculture. Succession on family farms is often a gradual process, in which management control is gradually transferred to the younger generation. The transfer of formal ownership is the last stage of the process, and may not take place until the death of the parent. The ‘holder’ in the Farm Survey is the person who assumes economic and legal responsibility for the farm and this will generally be the parent until a formal transfer of ownership is made.
The Farm Return used for the Farm Structure Survey distinguishes between holder and manager. The age data reported in the first table refer to the principal manger. If a son or daughter is the principal manager, it is his or her age that is reported. However, one wonders if this practice is always followed. The FSS data may give a more extreme view of the age distribution of management responsibilities, to the extent that these management responsibilities are shared with the younger generation and this is not picked up in the Survey.
The differences between the two sets of numbers are striking and support different narratives of the generational issue in agriculture. The FSS figures support the view that there is a severe generational renewal problem (with those over 65 outnumbering ‘young’ farmers by a factor of 4.6). Using the LFS data the age structure is still skewed towards older persons, but the number of ‘young’ people engaged in farming (defined somewhat more broadly as those under 40, and not confined to the farm operator) still exceeds older farmers (here defined as those 65 and over) by a factor of 1.4.
Conclusions – is there a growing policy problem?
Leaving aside these statistical issues, I want to make two points about the generational renewal issue in agriculture in this post. I accept that the age distribution in agriculture is skewed towards older age groups – this is an inevitable consequence of the falling numbers engaged in agriculture and thus a lower number of younger entrants compared to older exits. It is not a new phenomenon.
However, the perception that this problem is worsening, and that therefore we need to strengthen policies to address this issue, fails to take into account that the ageing of the European workforce is a general social phenomenon.
Fundamentally, it is linked to the changing demographic structure in Europe caused by lower fertility. This gives rise to a changing population pyramid in which the size of the younger age cohorts is falling relative to the size of the older age groups (see this Eurostat brief for a comparison of the EU-28 population pyramids in 2001 and 2016, Figure 4). It is also linked both to younger people staying longer in education, and older people remaining longer in the workforce due to improved health and rising longevity. If the ageing of the agricultural labour force is compared with general social trends, the case that there is a particular problem in agriculture does not stand up.
It may still be felt it would be desirable to mitigate the skewed age distribution in agriculture, and to encourage more younger farmers to enter farming or to take over management responsibility on the family farm where succession is involved. The second message of this post is that policy should learn from the striking differences across Member States in the extent of the problem before throwing EU money at new initiatives or renewing existing ones.
Some of these differences may reflect differences in farm structure (e.g. a greater proportion of smaller farms) which are not a policy lever in the short term. However, the differences may also reflect differences in policies with respect to inheritance practices, fiscal treatment, retirement schemes or the support given to succession within the family. It is striking to me that, in the extensive literature on the ‘young farmer’ problem, this cross-country analysis seems never to have been undertaken.
This post was written by Alan Matthews
Update 20 April 2018: The heading of the first table was changed to make clear it refers to the age structure of farm managers and not farm holders.
Picture credit: Robert Andrews, considered for his farming a model landowner by Arthur Young, with his wife, in a double portrait by Thomas Gainsborough, via Wikipedia, public domain.
Hi Alan, thanks for this interesting analysis
I recently toured the centre and south west of France doing surveys on this issue. The differences even within a single Member state regarding the potential for generation renewal are striking. There are areas where there is an incredible enthusiasm of the young generation to engage in farming, which did not seem to exist 10 years ago. In Cantal for example (a Less Favored mountain area which is not known for high agricultural incomes) it is a complete frenzy. Ag schools refuse students, and the pressure on land is enourmous (prices are incredibly high, at a point that can hardly been explained by returns to land, even if you consider the generous direct payments in the area). It looks llike one teenager out of two wants to be a farmer…. In Correze, a hundred kilometers South, there seem to be still some land abandonment, and fewer candidates, even though some (older) newcomers enter agriculture with small fruits, nuts, sometimes sheep production. Land prices are 1/4th of those in Cantal there.
This is hard to explain and we left the area without really understanding the reasons. Both areas are fit for extensive beef production, which consistently loses money, but both benefit heavily from direct payments which, in France, have been redirected towards animal production, more or less equally. Milk production is more or less abandoned in Correze while in Cantal there are some PGIs cheese that work a bit better. Cantal is closer to a big city where there is a good cultural life. TBut still, the economic rationale for such a difference is very weak. The difference in attracting young people in agriculture remains quite puzzling.
However, I see two reasons why the issue generation renewal is not as bad as it seems.
1- The Cantal case shows that nothing is decided for ever. Agriculture can just become as hype as the Kardashians within a decade.
2- A local ag adviser (and mother) gave us the solution for accurate predictions. She said that in Cantal, the most popular video game (played by almost every kid) is”Farming simulator” . Sales of Farming Simulator might be the best proxy for predicting generation renewal.
Amazingly, this video game was a bit of matter of joke a few years ago but it became at the end of 2016 one of top sales among all videogames in Europe: in 2017 “Farming Simulator 17 was number one for in-store sales on all platforms – so consoles included – on day one in Germany, which, clearly, loves farming games. It placed number three in Scandinavia, number four in France and number five in the UK”. https://www.eurogamer.net/articles/2016-11-25-well-at-least-one-games-smashed-sales-expectations-this-year
It could be one of the advanced proxy indicators that works… Forget Eurostat, just look at the sales of FS in every member state and you might get a better image of the generation renewal issue !
JC
Hi Alan
Thanks for the great and interesting analysis.
With respect to your plea for cross-country analyses into how dfferent situations in countries lead to a different degree of age skewness, in the SUREFARM project (http://surefarmproject.eu/) one of the aims is to do exactly that. We are looking at farm demographic patterns, how they differ between regions in different European countries, and which drivers and factors explain farm demographic change patterns. This study will be done by means of a qualitative research approach, interviewing different people (e.g., farmer, wife, son) within different farm businesses. Always happy to provide further information if you’re interested.
With respect to the comment made by Prof. Bureau, a recent interesting paper on farm succession is this one https://onlinelibrary.wiley.com/doi/abs/10.1111/soru.12s055 The authors show that farm succession is a socially constructed endogeneous cycle whereby succesor identity, farmer identity, succeedable farm identity are matched to each other. They suggest that the fact that maintaining this endogenous cycle is becoming increasingly difficult, is among the main reasons for low farm succession, and that most policies developed now don’t really tap into that. I read this very simply as the fact that the majority of farm children don’t develop a successor and farmer identity, and as long is this decrease continues, any policy directed at the last stage of succession, from the clear establishment of a successor and farmer identity to succession is likely to have little effects. In that sense, I can see how the popularity of the game Farming Simulator may have helped in restoring the endogenouc cycle of succesor identity development 🙂
I am also interested to explore the Labour Force Survey dataset and see how it differs from FSS. Do you happen to know whether the LFS dataset is disaggregated to, for instance NUTS 2 or NUTS 3 levels?
EW
I notice the link to the paper does not work properly, for some reason. Here is the reference Fischer, H., & Burton, R. J. (2014). Understanding farm succession as socially constructed endogenous cycles. Sociologia ruralis, 54(4), 417-438.