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Spatial Market Segmentation & Healthy Productive Landscapes Framework

Front cover of Spatial market segmentation Transaction types and trading segments in the water market

Transaction types and trading segments in the water market

Published by the Victorian Government Department of Primary Industries

Tatura, January 2009.

© Copyright State of Victoria, 2009

ISBN 978-1-74217-315-3

This publication is copyright. No part may be reproduced by any process except in accordance with the provisions of the Copyright Act 1968.

Authors:
Geoff Kaine# Ben Rowbottom#, Liz Morse-McNabb^ and Andy McAllister^
Farm Services Victoria Division# and
Future Farming Systems Research Division^
Department of Primary Industries
Private Bag 1
Ferguson Road
TATURA,   Victoria

Acknowledgments:
The authors would like to thank members of the project steering committee for their guidance and Wendy McAllister for her assistance composing this report.

Disclaimer:
This publication may be of assistance to you but the State of Victoria and its employees do not guarantee that the publication is without flaw of any kind or is wholly appropriate for your particular purposes and therefore disclaims all liability for any error, loss or other consequence which may arise from you relying on any information in this publication.

For more information about DPI visit the website at www.dpi.vic.gov.au
Or call the Customer Call Centre on 136 186.

If you would like to receive this information / publication in an accessible format (such as large print or audio) please call the Customer Service Centre on: 136 186, TTY: 1800 122 969, or email customer.service@dpi.vic.gov.au.

Table of contents

1.    INTRODUCTION

1.1.    SPATIAL MARKET SEGMENTATION

2.    MATERIALS & METHODS

  • 2.1.    COLLATION OF DATA
  • 2.2.    TRANSACTION TYPES AND TRADING SEGMENTS
    • 2.2.1. Classification of transaction types
    • 2.2.2. Classification of trading segments

3.    RESULTS

  • 3.1.    CHARACTERISTICS OF THE SAMPLE
  • 3.2.    CHARACTERISTICS OF TRANSACTION TYPES
    • Permanent purchases
    • Large and medium net temporary purchases
    • Medium and small temporary purchases
    • Small trades
    • Small, medium and large temp sales
    • Permanent sales
  • 3.3.    CHARACTERISTICS OF TRADING SEGMENTS
    • Segment 1: Regular small and medium temporary buyers
    • Segment 2: Occasional small temporary buyers
    • Segment 3: Small temporary buyers and sellers from 2003/04
    • Segment 4: Sporadic temporary buyers
    • Segment 5: Small traders
    • Segment 6: Temporary sellers from 2001/02
    • Segment 7: Regular small to medium temporary sellers
    • Segment 8: Regular medium and large temporary sellers

4.    DISCUSSION

5.    CONCLUSION

6.    REFERENCES

7.    APPENDIX A

8.    APPENDIX B

9.    APPENDIX C

Figures

FIGURE 1: DISTRIBUTION OF TRANSACTION TYPES OVER TIME (ALL TRANSACTIONS)

FIGURE 2: TRANSACTION TYPE PROFILE FOR SEGMENT ONE

FIGURE 3: TRANSACTION TYPE PROFILE FOR SEGMENT TWO

FIGURE 4: TRANSACTION TYPE PROFILE FOR SEGMENT THREE

FIGURE 5: TRANSACTION TYPE PROFILE FOR SEGMENT FOUR

FIGURE 6: TRANSACTION TYPE PROFILE FOR SEGMENT FIVE

FIGURE 7: TRANSACTION TYPE PROFILE FOR SEGMENT SIX

FIGURE 8: TRANSACTION TYPE PROFILE FOR SEGMENT SEVEN

FIGURE 9: TRANSACTION TYPE PROFILE FOR SEGMENT EIGHT

FIGURE A.1: DISTRIBUTION OF TRANSACTION TYPES 1998/1999

FIGURE A.2: DISTRIBUTION OF TRANSACTION TYPES 1999/2000

FIGURE A.3: DISTRIBUTION OF TRANSACTION TYPES 2000/2001

FIGURE A.4: DISTRIBUTION OF TRANSACTION TYPES 2001/2002

FIGURE A.5: DISTRIBUTION OF TRANSACTION TYPES 2002/2003

FIGURE A.6: DISTRIBUTION OF TRANSACTION TYPES 2003/2004

FIGURE A.7: DISTRIBUTION OF TRANSACTION TYPES 2004/2005

FIGURE A.8: DISTRIBUTION OF TRADING SEGMENTS

Tables

TABLE 1: DESCRIPTIVE STATISTICS FOR WATER TRADING BY THE SAMPLE OF 500 FARMERS

TABLE 2: PROFILES OF WATER TRADE TRANSACTION TYPES - SAMPLE

TABLE 3: PROFILES OF WATER TRADE TRANSACTION TYPES - ALL TRANSACTIONS

TABLE 4: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) - ALL TRANSACTIONS

TABLE 5: CHARACTERISTICS OF THE TRADING SEGMENTS

TABLE 6: PERCENTAGE OF TRADING SEGMENTS BY IRRIGATION REGION AND DISTRICT (%)

TABLE 8: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT ONE

TABLE 9: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT TWO

TABLE 10: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT THREE

TABLE 11: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT FOUR

TABLE 12: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT FIVE

TABLE 13: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT SIX

TABLE 14: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT SEVEN

TABLE 15: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – SEGMENT EIGHT

TABLE A.1: PROFILE OF WATER TRADE TRANSACTION TYPES (SAMPLE)

TABLE A.2: PROFILE OF WATER TRADE TRANSACTION TYPES (ALL TRANSACTIONS)

TABLE A.3: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) - SAMPLE

TABLE A.4: PERCENTAGE OF WATER TRADE TRANSACTION TYPES OVER TIME (%) – ALL TRANSACTIONS

1. Introduction

In a previous paper (Morse-McNabb et al. 2008), a method was developed to classify dairy farmers in the North Central (NC) and Shepparton Irrigation Region (SIR) into trading segments according to their transactions in the market for irrigation water over the six year period between 1996/1997 to 2003/2004.1 The classification method was based on patterns in transactions as measured by temporary and permanent purchases and sales averaged over the six-year period as a whole.  This method was limited in its usefulness as it could only be applied to landholders for whom data was available for the entire period of the analysis and any change in the period of the analysis would require complete reanalysis and reinterpretation of the trading segments (Morse-McNabb et al. 2008).

In this paper, we build on the previous study to develop a method for categorising transactions in the market for irrigation water in the North Central (NC) and Shepparton Irrigation Regions (SIR) into various types.  We then classify landholders into trading segments based on patterns in the transactions types and spatially map the segments.  This method offers greater flexibility than the original method as it allows trading segments to be identified over any time period based on patterns in a stable set of transactions types.  This means that an analysis of trading patterns need no longer be restricted to those landholders for whom data is available for the entire period of an analysis.

In this paper we apply the new method to updated information on transactions in the water market and include transactions involving horticultural, grazing and mixed enterprises as well as dairy enterprises in the analysis.

This project was a collaboration between the Department of Primary Industries Spatial Sciences Group and the Practice Change Research Group based at Tatura.

1.1. Spatial Market Segmentation

The concept of ‘spatial market segmentation’ brings together expertise in market segmentation with expertise in spatial mapping.  The idea is to use spatial mapping techniques to locate the members of market segments in the landscape.  The resulting maps may then be employed for a variety of purposes including measuring the size of segments and targeting policy programs.  Our use of spatial market segmentation stemmed from an investigation into the adoption of centre pivot technology by Hill et al. (2004).  They identified five primary factors that influenced farmers’ decision to adopt centre pivot technology, namely:

  • whether dairy farmers were likely to be redeveloping a block that was not previously part of the farm milking area
  • the topography of the block
  • the type of soils on that block
  • the distance of the block from the milking shed 
  • the type of forage to be grown on the block.

These factors were primarily biophysical in nature and measurable, in principle, for individual dairy farms in a landscape.  This raised the possibility that dairy farms exhibiting these factors could be located in the landscape using landscape data.  A pilot was conducted using existing Geographic Information System (GIS) data.  The pilot demonstrated that the size of the population of potential adopters of an innovation, CPT in this case, could be estimated using GIS techniques and the location of potential adopters in the landscape could be mapped (Hill et al. 2004).

The methods used in the Hill et al. (2004) study were extended by Morse-McNabb et al. (2008).  In that study, a population of dairy farmers were classified into segments using data on their transactions in the market for irrigation water.  The locations of the members of each segment were then mapped using GIS techniques.  This allowed a sample of farmers from each segment to be identified.  Techniques proposed by Kaine (2004) were then employed to discover the factors in the farm context that produced the pattern of transactions in each segment.

2. Materials & methods

2.1. Collation of data

Data on transactions in the water market by landholders in NC and SIR were made available by Goulburn-Murray Water (G-MW) through a data sharing agreement.  The data used in this analysis consisted of annual transactions for landholders over the seven-year period from 1998/1999 to 2004/2005.  Each transaction records the volume of water temporarily or permanently purchased, or sold, each year.  The analysis was based on the assumption that the type of land use (dairy, horticulture, grazing, mixed farming) did not change over the period of the analysis.  See Morse-McNabb et al. (2008) for further detail on the reliability of this assumption.

To maintain comparability with the earlier study on trading segments in the dairy industry, the analysis was restricted to those landholders for whom we had complete transaction records.  This limited the analysis to 5,819 of the 7,432 landholders for which transaction records were available (78 per cent).2 A further 2,154 landholders were excluded from the analysis because they could not be classified as dairy farmers, horticulturalists, grazing or mixed farmers.  This left data for 3,665 landholders available for analysis.  The data on landholder’s annual purchases and sales of temporary and permanent water were standardised by expressing purchases and sales as a percentage of their 1996/1997 entitlement.

2.2. Transaction types and trading segments

Our approach to identifying trading segments involved two steps.  In the first step, transactions by landholders in dairy, horticulture, grazing and mixed farming between 1998/1999 and 2004/2005 were categorised into types using cluster analysis (Aldenderfer & Blashfield 1989).  In the second step, landholders were classified into trading segments based on the types of transactions they made over the period between 1998/1999 and 2004/2005.

2.2.1. Classification of transaction types

In any particular season landholders may purchase or sell water, or both.  These purchases or sales may be temporary or permanent.  Clearly, the number of possible combinations of transactions is high even without considering the relative size of transactions.  Consequently, the first step in the analysis was to categorise the data on the sale and purchase of temporary and permanent water in each year into a relatively small number of easily interpretable transaction types.  This categorisation was done using cluster analysis employing Ward’s procedure with squared Euclidian distance as the similarity coefficient (Aldenderfer & Blashfield 1989) .  Ward’s procedure was chosen because the procedure creates hyper-spherical clusters that optimise the minimum variation within clusters, while maximising the distance between them (Aldenderfer & Blashfield 1989).3

Difficulties with data translation meant that this step in the analysis could not be applied to the entire set of 25,655 transactions (annual records over seven years for 3,665 landholders). Consequently, the analysis was based on 3,479 transactions drawn from a random sample of 497 landholders).4

A scree test (Aldenderfer & Blashfield 1989) indicated that a minimum of six types were present in the data.  The solutions for six to ten types were then inspected using descriptive statistics to determine the point where transactions that were qualitatively different from each other had been aggregated.  On the basis of this inspection we chose the solution involving ten transaction types as the most satisfactory, as this was solution where permanent purchases and permanent sales were identified as separate types of transactions.  The characteristics of the transaction types are described in Section 3.2.

Having identified a set of transaction types, the entire set of transactions (apart from those used in the cluster analysis) were categorised into types.  This was done by calculating the similarity between each transaction and the characteristics of each transaction type and allocating transactions to the type with which they were most similar. To ensure consistency with the cluster analysis, squared Euclidean distance was used as the similarity coefficient.

The reliability of this procedure was evaluated by applying the procedure to the random sample of landholders used in the cluster analysis.  The procedure categorised 95% of landholders into the same transaction type as the cluster analysis, indicating the procedure was reliable.  Furthermore, there were no significant differences between the sample and the complete data set in the proportion of each transaction type in each year (see Appendix A).5

The characteristics of the transaction types for the entire data set are described in Section 3.2.

2.2.2. Classification of trading segments

Having identified the ten types of transactions, landholders were then classified into water trading segments based on the types of transactions they made over the period between 1998/1999 and 2004/2005.  This involved converting the transaction data for each of the 3,665 landholders into a series of binary variables representing the type of transactions that the landholder had made in each year.  Landholders were then classified into market segments using cluster analysis.  Again, Ward’s procedure with squared Euclidian distance as the similarity coefficient was used (Aldenderfer & Blashfield 1989).

A scree test (Aldenderfer & Blashfield 1989) indicated that a minimum of five segments were present in the data.  The solutions for five to ten segments were then inspected using descriptive statics to identify the point where segments that were qualitatively different from each other had been aggregated.  The solution involving eight segments was chosen as the most satisfactory solution.  The characteristics of the segments are described in Section 3.3.

3. Results

3.1. Characteristics of the sample

The characteristics of the random sample of 497 landholders used in the categorisation of transactions are presented in Table 1.  The sample was made up of 98 landholders from NC and 399 landholders from the SIR.  As expected, statistical tests confirmed that the sample was representative of the 3,566 landholders in the complete data set.  For example, the proportion of landholders from each region and district in the sample was not statistically significantly different from the proportions from each region and district in the complete data set.6   The average volume of temporary water purchased and permanent water purchased or sold in the sample was not statistically significantly different from the averages in the complete data set.7   There was a statistical difference in the average volume of temporary water sold between the sample and the population, however this difference was trivial (less than one per cent).8   These results indicate the sample was representative of the complete data set.

3.2. Characteristics of transaction types

Ten types of transactions were identified from the random sample of landholders using cluster analysis.  The profiles of the different transaction types in terms of the average volume of temporary and permanent water purchased and sold within a year, relative to entitlement, are reported in Table 2.  The profiles of the different transaction types for the complete data set, excluding those from the random sample, are reported in Table 3.  Although there were statistically significant differences in the profiles of the transaction types for the random sample and the complete data set, a comparison of Tables 2 and 3 reveals these differences were slight and did not alter the interpretation of the types.  Our interpretation and description of the transaction types was based on the profiles for the entire set of transactions.

Permanent purchases

The first type of transaction consists almost entirely of permanent purchases by landholders.  On average, these transactions involved the permanent purchase by landholders of 137% of their 1996/1997 water entitlement (see Table 3).

Large and medium net temporary purchases

The next two transaction types consist of a combination of purchase and sales of temporary water, resulting in an overall net purchase of temporary water.  The difference between the two types of transactions is a matter of the size of the transactions relative to entitlement (see Table 3).

Medium and small temporary purchases

The next two transaction types consist almost entirely of transactions involving the purchases of temporary water.  The difference between the two types of transactions is the size of the transactions relative to entitlement (see Table 3).  An inspection of Table 3 reveals that these purchases were relatively small compared to the purchase transactions in the large and medium net temporary purchases (see Table 3).

Small trades

This transaction type consists of records for landholders that did not trade water, or traded very small amounts of temporary water relative to their 1996/1997 water entitlement (Table 2).  These transactions represented the majority of transactions in the data (63%).

Small, medium and large temp sales

These transactions consist almost entirely of transactions involving the sale of temporary water.  The difference between the three types of transactions is the size of the transactions relative to entitlement (see Table 3).

Permanent sales

The last type of transaction consists almost entirely of transactions involving the permanent sale of a relatively large proportion of the 1996/1997 water entitlement; approximately 73% on average (see Table 3).  Note that permanent sales and purchases represented less the 1% of all transactions (Table 3).

The proportion of transaction types in each year for all transactions is summarised in Table 4 and Figure 1.  There were significant differences in the proportions of transaction types in each year.9   Small trades make up the majority of transaction in every year; however the proportion of these transactions decreased over time, while the proportion of temporary water purchases and sales increased.

The spatial distribution of types of trades over time is presented in the maps contained in Appendix B.  An inspection of the maps reveals that trading was initially concentrated in the southern NC and SIR then spread northward over time.

3.3.    Characteristics of trading segments

The characteristics of the trading segments are summarised in Table 5.  There were significant differences in average water entitlement, water use and transaction behaviour among the segments.  There was a significant difference in the proportions of landholders in each segment from the NC and SIR and from irrigation districts within these regions (Table 6 and Appendix C).10   A statistically significant difference was also found in the proportion of landholders from dairy, horticulture, grazing and mixed farming in each segment (Table 7).11   These differences are discussed in the following descriptions of each segment (Sections 3.4.1-3.4.8).

Table 1: Descriptive statistics for water trading by the sample of 500 farmers

Table 2: Profiles of water trade transaction types - sample

Table 3: Profiles of water trade transaction types - all transactions

Table 4: Percentage of water trade transaction types over time (%) - all transactions

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0
0
0 0 0 0
2 Large net temp purchase 0 0 0 0 0 0 0
3 Medium net temp purchase 1 1 1 2 2 2 2
4 Medium temp purchase 3 3 4 5 4 6 7
5 Small temp purchase 11 13 11 12 13 16 15
6 Small trade 70 68 69 61 58 48 48
7 Small temp sale 6 6 7 9 12 10 11
8 Medium temp sale 4 5 5 5 9 8 8
9 Large temp sale 3 4 3 5 1 8 7
10 Permanent sale 0 1 0 1 1 2 1

No. of service IDs = 3165

Bar graph: Distribution of transaction types over time (all transactions)

Figure 1: Distribution of transaction types over time (all transactions)

Table 5: Characteristics of the trading segments


Trading segment
1 2 3 4 5 6 7 8 Total
Number of landholders 289 308 669 562 647 305 227 150 3 157
Percentage of landholders (%) 9 10 21 18 20 10 7 5 100
F-value p-value
Average water entitlement 96/97 (ML) 229 253 213 171 214 172 219 117 11.6 0.0
Average current water entitlement (ML) 232 252 200 160 217 168 207 101 13.3 0.0
Average water use 98/99 to 04/05 (ML) 2 499 2 300 1 916 1 265 1 676 886 1 047 186 53.9 0.0
Average volume temporary water purchased (ML) 901 410 167 121 25 45 39 29 347.0 0.0
Average volume temporary water sold (ML) 94 56 69 61 12 336 491 604 205.1 0.0
Average volume permanent water purchased (ML) 13 12 7 5 4 5 4 3 2.4 0.0
Average volume permanent water sold (ML) 9 10 17 14 7 6 13 15 2.1 0.0

Table 6: Percentage of trading segments by irrigation region and district (%)

Irrigation region/district Percentage per trading segment (%)
1 2 3 4 5 6 7 8 Total
Irrigation region
 North Central 4 7 31 15 28 9 5 2 100
 Shepparton 10 10 19 18 19 10 8 5 100
Irrigation district
 Boort 11 9 14 18 29 9 4 6 100
 Campaspe 10 5 15 49 10 3 8 0 100
 Central Goulburn 14 15 14 18 16 8 8 6 100
 Kerang-Cohuna 2 5 43 11 28 8 2 1 100
 Murray Valley 3 5 36 13 30 9 2 2 100
 Pyramid Hill 4 10 14 19 26 12 12 4 100
 Rochester 13 18 12 13 17 10 7 8 100
 Shepparton 11 6 12 27 13 13 13 6 100

Kerang-Cohuna district overlaps irrigation regions, and the separation of region is not for Kerang-Cohuna

Segment 1: Regular small and medium temporary buyers

This segment represented approximately 9 per cent of landholders and consisted of landholders who purchased small and medium volumes of temporary water every year (see Table 8, Figure 2).  Approximately 82% of transactions by these landholders were of the small and medium temporary purchase type.

A relatively small proportion of landholders in this segment were located in the NC region.12  Also, a relatively small proportion of these landholders were in the Kerang-Cohuna, Pyramid Hill and Murray Valley irrigation districts.  On the other hand, a relatively high proportion of landholders in the Rochester and Central Goulburn districts were in this segment (see Table 6 and Appendix C).13   A relatively high proportion of landholders in segment were dairy farmers (see Table 7).14

Segment 2: Occasional small temporary buyers

This segment represented approximately 10 per cent of landholders and consisted of landholders who purchased relatively small volumes of temporary water in 2000/2001, 2003/2004 and 2004/2005 and rarely traded in other years (see Table 9, Figure 3).

A relatively small proportion of landholders in this segment were located in the NC region.15    Also, a relatively small proportion of these landholders were in Kerang-Cohuna, Shepparton and Murray Valley.  On the other hand, a relatively high proportion of landholders in the Central Goulburn and Rochester districts were in this segment (see Table 6 and Appendix C).16   A relatively high proportion of dairy farmers were present in this segment (Table 7).17

Table 7: Percentage of trading segments by agricultural industry (%)

Agricultural industry Percentage per trading segment (%)
1 2 3 4 5 6 7 8 Total
Dairy 16 17 24 15 19 5 2 1 100
Horticulture 5 4 18 38 15 10 8 2 100
Grazing 2 3 27 16 32 12 4 4 100
Mixed 6 7 14 16 17 13 15 11 100

Table 8: Percentage of water trade transaction types over time (%) – segment one

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 1 0 1 2 1 0 2
3 Medium net temp purchase 6 8 6 17 11 11 10
4 Medium temp purchase 27 28 33 33 15 33 30
5 Small temp purchase 56 54 46 35 33 37 37
6 Small trade 8 7 12 10 30 7 10
7 Small temp sale 1 1 1 3 7 3 3
8 Medium temp sale 0 0 1 0 3 3 4
9 Large temp sale 1 0 1 0 0 4 3
10 Permanent sale 0 1 0 0 0 2 1

No. of service IDs = 289

Line graph: Transaction type profile for segment one

Figure 2: Transaction type profile for segment one

Table 9: Percentage of water trade transaction types over time (%) – segment two

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 1 0
2 Large net temp purchase 0 0 0 1 0 0 0
3 Medium net temp purchase 1 1 1 2 1 2 0
4 Medium temp purchase 5 3 5 6 5 6 8
5 Small temp purchase 19 35 53 45 19 59 47
6 Small trade 72 55 36 43 68 24 35
7 Small temp sale 1 5 3 2 5 4 4
8 Medium temp sale 2 0 1 1 2 2 2
9 Large temp sale 0 0 0 0 0 2 1
10 Permanent sale 0 0 0 0 0 1 2

No. of service IDs = 308

Line graph: Transaction type profile for segment two

Figure 3: Transaction type profile for segment two

Segment 3: Small temporary buyers and sellers from 2003/04

This segment represented 21% of landholders and consisted of landholders who, generally speaking, only began trading water in the 2003/04 season when they began purchasing or selling relatively small to medium volumes of temporary water (see Table 10, Figure 4).

A relatively high proportion of landholders from NC were in this segment.18 Also, a relatively high proportion of landholders in Kerang-Cohuna and Murray Valley were in this segment (Table 6 and Appendix C).19

Segment 4: Sporadic temporary buyers

This segment represented 17% of landholders and consisted of landholders who, generally speaking, did not trade in water except for purchasing a relatively small volume of temporary water in one or two years (see Table 11, Figure 5). Approximately 71% of all transactions by the landholders in this segment were of the small transaction type. Approximately 16% of transactions were small temporary purchases and 11% were small temporary sales transactions.

A relatively high proportion of landholders in the Campaspe and Shepparton irrigation districts were in this segment (Table 6 and Appendix C).20 A relatively high proportion of landholders in this segment were horticulturalists (Table 7).21

Table 10: Percentage of water trade transaction types over time (%) – segment three

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 0 0 0 0 0 0 0
3 Medium net temp purchase 0 0 0 1 1 0 2
4 Medium temp purchase 0 1 0 2 5 10 12
5 Small temp purchase 2 5 1 5 15 29 29
6 Small trade 95 90 95 87 73 31 20
7 Small temp sale 1 2 2 4 3 17 25
8 Medium temp sale 1 1 1 0 2 4 6
9 Large temp sale 1 1 1 1 0 3 4
10 Permanent sale 0 0 0 0 0 4 1

No. of service IDs = 669

Table 11: Percentage of water trade transaction types over time (%) – segment four

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 1 0 0 0 0 0 0
3 Medium net temp purchase 0 0 0 0 1 1 0
4 Medium temp purchase 1 2 2 3 7 2 1
5 Small temp purchase 21 18 5 15 22 4 2
6 Small trade 62 67 91 63 45 84 88
7 Small temp sale 8 6 1 12 13 5 3
8 Medium temp sale 3 4 1 4 8 4 2
9 Large temp sale 3 1 0 2 2 1 1
10 Permanent sale 1 2 1 1 2 0 2

No. of service IDs = 562

Line graph: Transaction type profile for segment three

Figure 4: Transaction type profile for segment three

Line graph: Transaction type profile for segment four

Figure 5: Transaction type profile for segment four

Segment 5: Small traders

This segment represented 20% of landholders and consisted of landholders who did not trade in water (see Table 12, Figure 6).  Approximately 71% of all transactions by the landholders in this segment were of the small transaction type. Approximately 16% of transactions were small temporary purchases and 11% were small temporary sales transactions.

A relatively high proportion of landholders in this segment were located in the NC region.22    A relatively high proportion of landholders in Boort, Kerang-Cohuna, Pyramid Hill and Murray Valley were in this segment while a relatively low proportion of landholders in Campaspe, Central Goulburn, Shepparton and Rochester were in this segment (Table 6 and Appendix C).23    A relatively high proportion of landholders in this segment were in the grazing industry (Table 7).24

Segment 6: Temporary sellers from 2001/02

This segment represented 10% of landholders and consisted of landholders who began selling temporary water from 2002/02 and onwards (see Table 13, Figure 7).  Initially, 80% of transactions by the landholders in this segment were of the small transaction type.  This proportion dropped to 49% in 2001/2002 and fell to only 9% in 2004/2005.  Over the seven years of the analysis, 44% of transactions conducted by this segment where small trades while 52% where temporary sales.

A relatively small proportion of landholders in this segment were in dairying, while a relatively high proportion of landholders were in grazing or mixed farming (Table 7).25

Table 12: Percentage of water trade transaction types over time (%) – segment five

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 0 0 0 0 0 0 0
3 Medium net temp purchase 0 0 0 0 0 0 0
4 Medium temp purchase 0 0 0 0 0 0 0
5 Small temp purchase 0 0 0 0 0 0 0
6 Small trade 100 100 100 100 100 100 100
7 Small temp sale 0 0 0 0 0 0 0
8 Medium temp sale 0 0 0 0 0 0 0
9 Large temp sale 0 0 0 0 0 0 0
10 Permanent sale 0 0 0 0 0 0 0

No. of service IDs = 647

Line graph: Transaction type profile for segment five

Figure 6: Transaction type profile for segment five

Table 13: Percentage of water trade transaction types over time (%) – segment six

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 0 0 0 0 0 0 0
3 Medium net temp purchase 0 0 0 0 0 1 0
4 Medium temp purchase 0 0 0 3 1 0 1
5 Small temp purchase 1 0 4 3 4 0 3
6 Small trade 79 75 73 49 15 10 9
7 Small temp sale 10 13 15 26 49 25 24
8 Medium temp sale 7 8 5 11 25 37 34
9 Large temp sale 2 3 2 9 6 27 26
10 Permanent sale 0 0 0 0 0 0 3

No. of service IDs = 305

Line graph: Transaction type profile for segment six

Figure 7: Transaction type profile for segment six

Segment 7:  Regular small to medium temporary sellers

This segment represented 7% of landholders and consisted of landholders who regularly sold relatively small volumes of temporary water (see Table 14, Figure 8).  Over the seven years of the analysis approximately 70% of all transactions for this segment were temporary sales.

A relatively small proportion of landholders in this segment were from the NC region.26   A relatively small proportion of landholders from Boort, Kerang-Cohuna and Murray Valley were in this segment.  In contrast, a relatively high proportion of landholders from Pyramid Hill and Shepparton were in this segment (Table 6 and Appendix C).27   A relatively high proportion of landholders in this segment were mixed farmers while relatively small proportions were in dairying and grazing (Table 7).28

Segment 8: Regular medium and large temporary sellers

This segment represented 5% of landholders and consisted of landholders who regularly sold relatively large volumes of temporary water (see Table 15, Figure 9). Over the seven years of the analysis, approximately 85% of all transactions for this segment were temporary sales.

A relatively small proportion of landholders in this segment were from the NC region.29    A relatively small proportion of landholders from Campaspe, Kerang-Cohuna and Murray Valley were in this segment.  In contrast, a relatively high proportion of landholders from Central Goulburn, Rochester and Shepparton were in this segment (Table 6 and Appendix C).30    A relatively high proportion of landholders in this segment were mixed farmers (Table 7).31

Table 14: Percentage of water trade transaction types over time (%) – segment seven

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 0 0 0 0 0 0 0
2 Large net temp purchase 0 0 0 0 0 0 0
3 Medium net temp purchase 0 0 0 0 1 0 0
4 Medium temp purchase 0 0 0 0 0 0 1
5 Small temp purchase 2 0 0 0 7 2 2
6 Small trade 27 33 4 22 41 27 30
7 Small temp sale 41 34 61 37 30 30 22
8 Medium temp sale 26 26 32 34 19 30 33
9 Large temp sale 4 7 2 3 0 9 8
10 Permanent sale 0 0 0 4 1 1 4

No. of service IDs = 227

Line graph: Transaction type profile for segment seven

Figure 8: Transaction type profile for segment seven

Table 15: Percentage of water trade transaction types over time (%) – segment eight

Water trade transaction type Percentage of transaction types conducted in each year (%)
98/99 99/00 00/01 01/02 02/03 03/04 04/05
1 Permanent purchase 1 1 0 0 0 0 0
2 Large net temp purchase 0 0 0 0 1 1 0
3 Medium net temp purchase 0 1 1 0 1 0 1
4 Medium temp purchase 1 0 0 0 0 0 1
5 Small temp purchase 1 0 0 1 1 0 1
6 Small trade 21 13 9 4 3 11 15
7 Small temp sale 9 8 3 4 19 9 5
8 Medium temp sale 24 22 30 17 65 7 11
9 Large temp sale 44 56 57 75 7 64 63
10 Permanent sale 0 0 0 0 3 8 3

No. of service IDs = 150

Line graph: Transaction type profile for segment eight

Figure 9: Transaction type profile for segment eight

4. Discussion

The results reported here indicate that the market for irrigation water is complex and dynamic, consisting of a variety of segments that are changing over time.  The results revealed that an increasing proportion of landholders were participating in the market over time.  This increase may be caused by a number of factors including:

  • drought and reduced allocations of water for irrigation
  • experience  with water trading
  • trading in unused irrigation licences (sleeper licences)
  • the increase in the value of irrigation water over time
  • variations in market condition for agricultural products
  • changes in the use of perennial pasture and annual fodder crops in the dairy industry.

It seems likely that the importance of these factors will vary across the trading segments.  Differences in the factors influencing the trading segments could be investigated by interviewing landholders from each segment.  The integration of the market segmentation with spatial mapping would allow a sample of landholders in each segment to be easily identified for such a purpose.  This was demonstrated by Morse-McNabb et al. (2008), who employed this approach to investigate the relationship between use of perennial pasture and water trading by dairy farmers.

The results also revealed that:

  • an increasing proportion of farmers were trading temporary water
  • only a very small proportion of farmers traded permanent water
  • there is considerable variation in the frequency of landholder participation in the market with some participating in the market regularly while others participated only occasionally
  • there is considerable variation in the trading behaviour of landholders, with some being regular sellers of water while others were regular buyers of water. Relatively few landholders bought and sold water.

The results also revealed that water tended to be traded from grazing and mixed farming to dairy and horticulture and this was reflected in the spatial variation in market segments across irrigation districts.  This variation seemed consistent with conventional wisdom on the differences in the relative value (and elasticity of demand) for water among these industries.

The results also revealed that the trading segments in the water market are highly dynamic.  For example, landholders in some segments in our analysis only traded water in one or two particular years.  This dynamism means the nature and composition of trading segments in the water market can be expected to change constantly over time.  We have shown that  that the variety in the trading behaviour of landholders in the water market can be can summarised and understood by categorising transactions in the water market into a conveniently small number of stable transaction types.

The integration of market segmentation with spatial mapping techniques also provides a means of monitoring the impact of trades in the water market on key environmental assets.  The placement in the landscape of landholders in each market segment allows the transfer of water as a result of market transactions to be visualised within and across regions and districts.  This means the impact of market transactions on key environmental and economic assets can be traced and evaluated.

5. Conclusion

In this study we have developed and demonstrated a method for identifying trading segments in the market for irrigation water in the NC and Shepparton irrigation regions.  The method is based on categorising the transaction in the water market into a conveniently small number of types.  This categorisation provides a stable platform for identifying and interpreting trading segments in the highly dynamic water market. 
The method, by integration with spatial mapping techniques, also allows individual members of trading segments to be located in the landscape.

The method offers a number of benefits including the ability to easily update trading segments with new transaction data and to monitor changes in trading segments over time and across landscapes.  The method also has the potential to allow trading behaviour of landholders to be linked with their circumstances.  Finally, the method offers the potential to monitor and evaluate the impact of water trading on key environmental and economic assets in irrigation regions.

6. References

Aldenderfer M.S. and Blashfield R.K. (1989). Cluster Analysis – Series: Quantitative Applications in the Social Sciences. Sage Publications: London.

Hill M., Linehan C. and Murdoch H. (2004). Efficient Irrigation Technologies to Match Soils and Dairy Farming Systems, Market Research Report. Department of Primary Industries, Tatura.

Morse-McNabb, E., McAllister, A., Kaine, G., Rowbottom, B., Linehan, C. (2008). Spatial Market Segmentation & Healthy Productive Landscapes Framework. A Report for the North Central and Goulburn Broken Catchment Management Authorities.  Department of Primary Industries, Tatura.

Kaine, G. (2004). Consumer Behaviour as a Theory of Innovation Adoption in Agriculture. Social Research Working Paper, 01/04. AgResearch, NZ.

7. Appendix A

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8. Appendix B

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9. Appendix C

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Footnotes

1 Groups such that landholders exhibiting similar characteristics are in the same group, while landholders exhibiting different characteristics are in different groups

2 Assuming each service ID represented a single landholder.

3 Available in SPSS 12.0.1

4 Using SPSS 12.0.1, select random cases function.

5 Permanent Purchase x2 = 5.13, p = 0.44; Large Net Temp Purchase x2 = 1.78, p = 0.95; Medium Net Temp Purchase x2 = 6.45, p = 0.36; Medium Temp Purchase x2 = 1.17, p = 0.98; Small Temp Purchase x2 = 5.73, p = 0.45; Small Trade x2 = 0.64, p = 0.99; Small Temp Sale x2 = 1.74, p = 0.94; Medium Temp sale x2 = 6.66, p = 0.35; Large Temp sale x2 = 6.50, p = 0.37; Permanent sale x2 = 3.39, p = 0.76.

6 x2 = 0.47, p = 0.49; x2 = 2.86, p = 0.84 respectively.

7 Temporary water purchased t = 0.67, p = 0.50; Permanent water purchased t = -0.20, p = 0.84; Permanent water sold t = -0.26, p = 0.79.

8 Temporary water sold t = -2.61, p = 0.01.

9 x2 = 99.7, p = 0.00

10 x2 = 95.6, p = 0.00 for region and x2 = 680.5, p = 0.00 for district respectively.

11 x2 = 703.0, p = 0.00

12 x2 = 95.56, p = 0.00

13 x2 = 680.5, p = 0.00

14 x2 = 703.0, p = 0.00

15 x2 = 95.6, p = 0.00

16 x2 = 680.5, p = 0.00

17 x2 = 703.0, p = 0.00

18 x2 = 95.6, p = 0.00

19 x2 = 680.5, p = 0.00

20 x2 = 680.5, p = 0.00

21 x2 = 703.0, p = 0.00

22 x2 = 95.6, p = 0.00

23 x2 = 680.5, p = 0.00

24 x2 = 703.0, p = 0.00

25 x2 = 703.0, p = 0.00

26 x2 = 95.56, p = 0.00

27 x2 = 680.5, p = 0.00

28 x2 = 703.0, p = 0.00

29 x2 = 95.6, p = 0.00

30 x2 = 680.5, p = 0.00

31 x2 = 703.0, p = 0.00