insolvency: Insolvency data
In EffectStars2: Effect Stars

Description Format Source References Examples

The data set originates from the Munich founder study. The data were collected on business founders who registered their new companies at the local chambers of commerce in Munich and surrounding administrative districts. The focus was on survival of firms measured in 7 categories, the first six represent failure in intervals of six months, the last category represents survival time beyond 36 months.

A data frame with 1224 observations on the following 16 variables.

Insolvency: Survival of firms in ordered categories with levels 1 < 2 < 3 < 4 < 5 < 6 < 7
Sector: Economic Sector with levels industry, commerce and service industry
Legal: Legal form with levels small trade, one man business, GmBH and GbR, KG, OHG
Location: Location with levels residential area and business area
New_Foundation: New Foundation or take-over with levels new foundation and take-over
Pecuniary_Reward: Pecuniary reward with levels main and additional
Seed_Capital: Seed capital with levels < 25000 and > 25000
Equity_Capital: Equity capital with levels no and yes
Debt_Capital: Debt capital with levels no and yes
Market: Market with levels local and national
Clientele: Clientele with levels wide spread and small
Degree: Educational level with levels no A-levels and A-Levels
Gender: Gender with levels female and male
Experience: Professional experience with levels < 10 years and > 10 years
Employees: Number of employees with levels 0 or 1 and > 2
Age: Age of the founder at formation of the company

Muenchner Gruender Studie

Bruederl, J. and Preisendoerfer, P. and Ziegler, R. (1996): Der Erfolg neugegruendeter Betriebe: eine empirische Studie zu den Chancen und Risiken von Unternehmensgruendungen, Duncker & Humblot.

## Not run: 
data(insolvency)
insolvency$Age <- scale(insolvency$Age)

my_formula <- Insolvency ~ Age + Gender

m_acat <- vglm(my_formula, data = insolvency,family = acat())
m_cratio <- vglm(my_formula, data = insolvency,family = cratio())
m_sratio <- vglm(my_formula, data = insolvency,family = sratio())
m_cumulative <- vglm(my_formula, data = insolvency,family = cumulative())

summary(m_acat)
effectstars(m_acat, p.values = TRUE)

summary(m_cratio)
effectstars(m_cratio, p.values = TRUE)

summary(m_sratio)
effectstars(m_sratio, p.values = TRUE)

summary(m_cumulative)
effectstars(m_cumulative, p.values = TRUE)

## End(Not run)