IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Research article
erd

Does the Downward Trend of the Farming Population in
Remote and Mountainous Areas Increase the Average Farm
Size? A Community Level Data Analysis in Tohoku Region,Japan
SHIGEKAZU KAWASHIMA*
Department of Food Resource Development, Faculty of Food Industrial Science,
Miyagi University, Japan
Email: kawashim @myu.ac.jp

ASATO MIZUKI
Department of Environmental and Resource Economics, Graduate School of Agricultural
Science, Tohoku University, JapanFUSAO ITO
Department of Environmental and Resource Economics, Graduate School of AgriculturalScience, Tohoku University, Japan
Received 20 January 2020

Accepted 23 May 2020(*Corresponding Author)

Abstract Over the last several decades, Japan’s farming population has gradually decreased
and the average age of farmers has risen. The recent agricultural census 2015 indicated that
there were 2.09 million people engaged in agriculture, which is a reduction of 60% comparedto three decades earlier. The decline in farming populations is robust and is taking place inmany agricultural communities in Japan. However, the impacts of the declining farming
population differ significantly on the basis of the conditions of farming land. Retirement ofaged farmers provides farming opportunities for young, local farmers, consequently leading
to an expansion in the size of farms. In fact, the average farm size per household in Japan
doubled from 1.05 ha in 1985 to 2.20 ha in 2015. This represents a positive aspect of aging
and the decreasing farming population. On the other hand, farmland abandonment has beenprominent in the last 30 years, accounting for nearly 10% of total farmland. In the remote andmountainous areas of Japan, maintaining agricultural activities is increasingly difficult,thereby casting doubt on the sustainability of agricultural production and rural communities.
In such a case, the average farm size does not increase, weakening rural economies andcommunities. This study uses approximately 14,000 community-level data in the Tohoku
region of Japan and examines the land conditions that induce an increase in average farmsize. The land conditions we consider are (1) steepness, (2) elevation, and (3) time-distancefrom a city. Quantile regression analysis is carried out to identify land conditions and othersocio-economic variables associated with average farm size. Our regression analysis
indicates that farm size does not necessarily increase where farm sizes are initially small,even in the case of declining farming population. Discussion within agricultural communities
to build trust and consensus on distributional conflicts are considered to be an effective
countermeasure to increase farm sizes in remote and mountains areas. The empirical evidence
suggests the need for varied policy interventions in accordance with land conditions.
Keywords farm size, agricultural community, quantile regression, farmland abandonmentINTRODUCTION
Family farmers in different locations face different constraints to agricultural development. In Asia,
it can be generalized that land scarcity has been the most serious constraint, although this can beaddressed through increasing land productivity at an initial stage of agricultural development (FAO,2014). As land productivity increases with the use of fertilizer, pesticide, irrigation, and the use ofⒸ ISERD187

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

modern technology, labor scarcity becomes the next most serious constraint, to which mechanicaltechnologies are adapted to reduce labor cost. As labor moves from the agricultural sector to nonagricultural sectors, increasing labor productivity of the remaining farmers becomes vitally important
to maintain farm incomes. This is the second phase of agricultural development. Many Asian
countries, including Japan, are now in the second phase of agricultural development (FAO, 2014).
Priority has shifted from increasing land productivity to increasing labor productivity and farmers’
incomes, which requires increasing farm size. The question to be asked is whether the average farmsize has been increasing in accordance with the downward trend of the farming population.
The recent agricultural census 2015 indicated that 2.09 million people engaged in agriculture,
which represents a decrease of 60% compared to three decades earlier (MAFF, 2018). The decline
in the farming population is robust and is taking place in many agricultural communities in Japan. A
declining farming population has both positive and negative impacts on rural communities. On thepositive side, there are increased opportunities to expand the farming size because the retirement ofaged farmers generally provides farming opportunities with neighborhood and/or young farmers,
consequently leading to an expansion in farming size. In fact, the average farm size per household inJapan doubled from 1.05 ha in 1985 to 2.20 ha in 2015 (MAFF, 2018). However, farmland
abandonment has also been prominent in the last 30 years, accounting for nearly 10% of total
farmland (MAFF, 2018). When farmland is not taken over by farmers of the next generation,
maintaining agricultural activities becomes increasingly difficult, thereby casting a doubt on thesustainability of agricultural production and rural communities. It is highly important to preserve thefarm and possibly to increase the farm size. Only a few studies have been carried out to examine thecorrelation among farm size, socio-economic variables, and community variable (Akimowicz. et.al,2013), empirical analysis with larger datasets is still insufficient. Therefore, this study examines thesocio-economic conditions under which farmers in rural communities increase farm sizes. Utilizing
GIS datasets for the Tohoku Region of Japan, including elevation, slope, and time-distance to thecity, along with other community variables such as the number of community meetings and thepercentage of rural population over 65, we investigate the determinants of farm size.
MATERIALS AND METHOD
Data and Agricultural Community
Table 1 Basic statistics
Variablenotation

Means.d.

minmax

Farm size in 2015

y2015

2.38

1.68

0.075

25

Farm size in 2010

y2010

2.12

1.42

0.1

25

Elevation (100m)

z1

1.425

1.357

0.004

9.055

Slope

z2

2.57

2.58

020

Time-distance: 30 to 60 minutes

z30.260.44

01Time-distance: 60 to 90 minutes

z4

0.04

0.20

01Time-distance: over 90 minutes

z50.010.08

01# of community meetings (CM)

x1

14.14

12.02

099

# of issues discussed at CMx2

4.42

1.70

06% of rural population over 65

x3

0.34

0.08

01

# of incorporated farm

x4

0.07

0.30

05

Average Farm Size

GIS Variables

Community Variables

This study uses Agricultural Census Datasets for 2015 and 2010 for the Tohoku Region of Japan (seeTable 1). The total sample is 14,253. The datasets include average farm size, elevation, slope, timeⒸ ISERD188

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

distance to the nearest city, and community variables. Community variables are included to identify
socio-economic characteristics that induce an expansion in farming size. We hypothesize that thatthe number and quality of community meetings, as well as mutual trust within the community, makeland transactions easier, thereby contributing to increases in average farm size.
Table 2 shows the average farm size by elevation and slope. It indicates that the average farm
size is larger at lower elevations and where farmland is flatter. It also shows smaller increases inaverage farm size for farmland located in steeper mountainous area. This implies that farmland
located in the remote and mountainous areas is more likely to be abandoned rather than handed tothe next generation.
Table 2 Change in average farm size by elevation and slope from 2010 to 2015
Slope (θ): z2(flat)(high)
A:Farm Size (ha) in2015

Elevation(m)：z1(steep)

2.59

2.14

1.59

1.38

2.54

1.83

1.68

1.44

2.08

2.23

1.88

1.63

(low)

2.76

2.34

1.94

1.82

(high)

2.35

1.98

1.54

1.31

2.26

1.69

1.57

1.31

1.84

2.03

1.74

1.53(low)

2.40

2.07

1.84

1.57

(high)

10.2

8.1

3.7

5.8

12.3

8.4

6.6

10.2

13.3

10.1

7.9

6.9

14.9

13.0

5.5

16.5

B:
Farm Size (ha) in2010（A-B)/B*100(% Change)(low)

Statistical Analysis
The distribution of farm sizes across agricultural communities is highly skewed and asymmetrical.
Therefore, the results from a standard regression analysis (i.e. ordinary least squares) are biased andcannot provide a comprehensive picture of the effect of the independent variables on the dependentvariable. In this study, quantile regression analysis is employed to observe the different effects ofeach explanatory variable along the distribution of the dependent variable. The estimated equation isdefined as (1).
𝛼 is a constant term, and 𝛽 captures the effect from average farmland size in 2010. 𝛾𝑖 measures theeffect of GIS variables on the average farmland size in 2015. 𝑥𝑗 represents socio-economic
community variables. These are included to examine socio-economic characteristics that areassociated with farmland size. Since community variables might be considered as endogenousvariables, we report the estimation results with and without the community variables.
RESULTS AND DISCUSSION
Table 3 shows the results of the quantile regression analysis. The effects of average farm size in 2010
on the average farm size in 2015 are dependent on the quantile estimated. With a smaller farm size
(quantile 25%), the estimated coefficients turn out to be 0.96-0.97, less than 1.0, meaning that
average farm size is more likely to decrease by 3 to 4% every five years. On the other hand, with alarger farm size (quantile 75%), the estimated coefficients are more than 1.0, which indicates that theaverage farm size increases by about 22% when assuming other variables are constant. Thus, theⒸ ISERD189

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

aged population and general decrease of the farming population contributes only to agriculturalcommunities where the average farm size is already high. In other words, agricultural communities
in the remote and mountainous areas, often with their smaller farm sizes, do not make use ofadditional farming opportunities, weakening overall agricultural activity.
Table 3 Results of quantile regression
Dependent variable: Average farm size in 2015
With community variable

Without community variable

Quantile

Quantile

Variable

25%

50%

75%

25%

50%

75%

Average farm
size in 2010

0.960***

1.081***

1.222***

0.967***

1.083***

1.223***

Elevation
Slope
Time-distance:
30 to 60
Time-distance:
60 to 90
Time-distance:over 90# of meetings(177.06)(187.98)(160.64)(166.13)(188.37)(161.94)-0.007***-0.009***-0.013***-0.008**-0.009***-0.013***(-2.79)(-3.24)(-3.03)(-2.46)(-3.02)(-3.18)-0.008***-0.006***-0.007***-0.009***-0.007***-0.006***(-7.03)(-4.78)(-3.14)(-6.4)(-4.64)(-3.11)0.008-0.005-0.0070.005-0.007-0.004(1.02)(-0.58)(-0.57)(0.6)(-0.84)(-0.32)-0.007-0.001

0.016-0.031-0.0030.031(-0.29)(-0.08)(0.51)(-1.26)

-0.19

1.06

0.017

0.033

0.045

0.019

0.037

0.054

(0.36)(0.93)(0.64)(0.52)(0.7)(0.66)

0.002***

0.001***

0.0005(8.71)(3.69)(0.90)# of issues
discussed

0.006***

0.002

0.001

(2.80)(0.91)(0.37)% of population
over age 65-0.239***-0.0630.092(-6.25)(-1.65)(1.34)# ofincorporated
farmland0.025*

0.012

0.006

(1.85)(0.75)(0.36)

0.046***

0.011

0.008

0.009

0.015

0.049***(2.62)
0.561(0.61)
0.617(0.26)
0.632(0.81)
0.559(1.40)
0.616(3.03)
0.632

Constant
Pseudo R2

N
14,235
14,235∗∗∗, ∗∗, and ∗ indicate statistical significance at the 1%, 5%, and 10% levels, respectively.

This study investigates geographic and socio-economic conditions that induced an increase infarm size in rural Japan. Community level data analysis indicates that the average farm size does notnecessarily increase as the farming population decreases, particularly where the average farm size isinitially small. Some farmland in the remote and mountainous areas of Tohoku Region has beenabandoned rather than passed down to the next generation. Farmland on steeper slopes at higher
elevations is more expensive to operate than in the lowland, meaning that consolidating farmland
does not provide sufficient economic benefits in mountainous areas. Our regression analysis also
shows that frequent community gatherings to discuss local issues and the establishment ofincorporated farmland within the community would help increase the farm sizes. Fostering trust
through engagement reduces transaction costs and encourages the establishment of cooperatives orincorporated farms, which may account for an increase in farm size.
Furthermore, the effects of elevation and slope on average farm size are always negative andⒸ ISERD190

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

significant, particularly at the 25% quantile (smaller farm size). Land condition represented bysteepness and a mountainous area always impair the expansion of farm size. Lower elevation andflatter farming areas are key conditions that accelerate land transactions, thus resulting in higher
average farm sizes.
The sign of the percentage of people above 65 years of age is positive at the 75% quantile andnegative and significant at the 25% quantile. The retirement of aged farmers generally provides
opportunities for younger farmers. Such opportunities are not taken advantage of where the averagefarm size is generally smaller (25% quantile). The sign of the number of incorporated farms turns
out to be positive and significant only at the 25% quantile, indicating that the small number ofincorporated farms in the highlands may contribute to the expansion in farm size throughconsolidating farmland within the community.
Both the number of community meetings and the number of issues discussed in these meetingshave a positive effect on the average farm size at the 25% quantile. It is important to note that
discussion within the agricultural community allows for building mutual trust and mitigating
distributional conflict, thus leading to a reduction of overall transaction costs.
CONCLUSION
This study investigates geographic and socio-economic conditions that fostered an increase inaverage farm sizes in rural Japan. Community level data analysis indicates that the average farm size
does not necessarily increase as the farming population decreases, particularly where average thefarm size is still small. Some farmland in the remote and mountainous areas have been abandoned
rather than handed to the next generation. Farmland on higher slopes at higher elevation is more
expensive to operate than in the lowlands, meaning that consolidation of farmland does not provide
sufficient economic benefit. Our regression analysis also shows that frequent community gatherings
to discuss local issues and establishment of incorporated farms within the community would help
increase the farming size. Fostering trust through discussions has reduced transaction costs andencouraged the establishment of cooperatives or incorporated farm, possibly resulting in an increasein farming size.
ACKNOWLEDGEMENTS
This work was supported by JSPS KAKENHI Grant Number JP17K07986.
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