東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Financial instability in agriculture...

Franks, Jeremy R.

Linked to FindBook

Google Book

Amazon

博客來

Financial instability in agriculture: Definition, identification and causes.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Financial instability in agriculture: Definition, identification and causes./
Author:	Franks, Jeremy R.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 1996,
Description:	334 p.
Notes:	Source: Dissertations Abstracts International, Volume: 79-02, Section: C.
Contained By:	Dissertations Abstracts International79-02C.
Subject:	Agriculture. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10648400
ISBN:	9780355226225

Financial instability in agriculture: Definition, identification and causes.
Franks, Jeremy R.

Financial instability in agriculture: Definition, identification and causes. - Ann Arbor : ProQuest Dissertations & Theses, 1996 - 334 p.

Source: Dissertations Abstracts International, Volume: 79-02, Section: C.

Thesis (Ph.D.)--The University of Manchester (United Kingdom), 1996.

The concept of financial instability employed in this study focuses on the degree of independent financial control retained by the proprietor, this definition implies that the most extreme form of financial stress is enforced bankruptcy. Alternative measurements of this concept are presented. The distributions of farms classified by these measurements are obtained for 105 identical farms extracted from the Farm Business Survey database from 1983/84 to 1990/91. It is argued that rental equivalent to gross margin is the most appropriate measure of financial instability. Values of this measure are used to separate the sample of farms into three categories: stable, vulnerable and stressed. The multinomial logit functional form is used as a discriminant function to select characteristic variables that predict the financial stress of farms in the following year(s). The identification of variables that characterise farms in different future stress categories is aided by a literature review, analyses of means tests and principle component analysis. A study of aggregate farm business bankruptcy in England and Wales suggested that the sector's terms of trade is an important causal variable of aggregate bankruptcy rates, this variable is included in the MNL model. The analysis of aggregate bankruptcy indicated a long run relationship exists between the rate of bankruptcy, agricultural assets and liabilities. The variables selected by the multinomial logit model to indicate likely future levels of financial stress form four categories, those directly under the farmer's management; assets, liabilities, profit, variable costs, value of farm output, the returns to assets and equity, those that are individual to the farmer; access to private equity; those that are structural in nature; land ownership, farm type and location; and a summary of the sector's trading position, the sector's terms of trade. Farm type and the level of liabilities are shown to have the most impact on the probability of being classified as financially stressed in the following year. This analysis indicates that the actions most commonly taken by farmers to relieve financial stress, that of increasing the use of variable inputs, is a sub-optimal response, the appropriate action is to reduce external liabilities, even if this involves selling capital assets. To analyze the profile of financial decline the categories of the dependent variable are redefined. Observations are allocated into one of five categories, stable in all years, observations that are either one, two or three years prior to being classified as stressed and those farms actually stressed. Distinct trends in the symptoms of stress, (e.g. occupiers income, value of farm produce and liabilities) and reactions to that stress (e.g. disinvestment and debt structure) are shown. A MNL model is specified to predict if an observation is likely to be in either the stable, stressed or the 'declining' category (formed from joining the one, two and three years categories) in the following year. This model confirms that increasing working assets and variable costs does not significantly reduce the probability of experiencing financial stress.

ISBN: 9780355226225Subjects--Topical Terms:

518588
Agriculture.
Subjects--Index Terms:

Bankruptcy

Financial instability in agriculture: Definition, identification and causes.
LDR:04291nmm a2200337 4500 001 2400725
005 20240930130020.5
006 m o d
007 cr#unu||||||||
008 251215s1996 ||||||||||||||||| ||eng d
020 $a 9780355226225
035 $a (MiAaPQ)AAI10648400
035 $a (MiAaPQ)RLUKUniversityofManchesterM0022
035 $a AAI10648400
040 $a MiAaPQ $c MiAaPQ
100 1 $a Franks, Jeremy R. $3 3770779
245 1 0 $a Financial instability in agriculture: Definition, identification and causes.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 1996
300 $a 334 p.
500 $a Source: Dissertations Abstracts International, Volume: 79-02, Section: C.
500 $a Publisher info.: Dissertation/Thesis.
502 $a Thesis (Ph.D.)--The University of Manchester (United Kingdom), 1996.
520 $a The concept of financial instability employed in this study focuses on the degree of independent financial control retained by the proprietor, this definition implies that the most extreme form of financial stress is enforced bankruptcy. Alternative measurements of this concept are presented. The distributions of farms classified by these measurements are obtained for 105 identical farms extracted from the Farm Business Survey database from 1983/84 to 1990/91. It is argued that rental equivalent to gross margin is the most appropriate measure of financial instability. Values of this measure are used to separate the sample of farms into three categories: stable, vulnerable and stressed. The multinomial logit functional form is used as a discriminant function to select characteristic variables that predict the financial stress of farms in the following year(s). The identification of variables that characterise farms in different future stress categories is aided by a literature review, analyses of means tests and principle component analysis. A study of aggregate farm business bankruptcy in England and Wales suggested that the sector's terms of trade is an important causal variable of aggregate bankruptcy rates, this variable is included in the MNL model. The analysis of aggregate bankruptcy indicated a long run relationship exists between the rate of bankruptcy, agricultural assets and liabilities. The variables selected by the multinomial logit model to indicate likely future levels of financial stress form four categories, those directly under the farmer's management; assets, liabilities, profit, variable costs, value of farm output, the returns to assets and equity, those that are individual to the farmer; access to private equity; those that are structural in nature; land ownership, farm type and location; and a summary of the sector's trading position, the sector's terms of trade. Farm type and the level of liabilities are shown to have the most impact on the probability of being classified as financially stressed in the following year. This analysis indicates that the actions most commonly taken by farmers to relieve financial stress, that of increasing the use of variable inputs, is a sub-optimal response, the appropriate action is to reduce external liabilities, even if this involves selling capital assets. To analyze the profile of financial decline the categories of the dependent variable are redefined. Observations are allocated into one of five categories, stable in all years, observations that are either one, two or three years prior to being classified as stressed and those farms actually stressed. Distinct trends in the symptoms of stress, (e.g. occupiers income, value of farm produce and liabilities) and reactions to that stress (e.g. disinvestment and debt structure) are shown. A MNL model is specified to predict if an observation is likely to be in either the stable, stressed or the 'declining' category (formed from joining the one, two and three years categories) in the following year. This model confirms that increasing working assets and variable costs does not significantly reduce the probability of experiencing financial stress.
590 $a School code: 1543.
650 4 $a Agriculture. $3 518588
650 4 $a Classification. $3 595585
653 $a Bankruptcy
690 $a 0503
690 $a 0473
710 2 $a The University of Manchester (United Kingdom). $b Department not provided. $3 3768924
773 0 $t Dissertations Abstracts International $g 79-02C.
790 $a 1543
791 $a Ph.D.
792 $a 1996
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10648400