예제 #1
0
summary_by_age.to_excel(writer, 'eff_score_by_age')

#malmquist index
# how many firms grow over time? pc>1
df = preda.read_malmquist('malmquist_machinery.csv')

df_mac = preda.read_malmquist('malmquist_tovrs_mac.csv')

df_compare = preda.encode_change(df, 241, 41, 23)
growth_dmu = preda.growth_dmu(df_compare, 307)
efficiency_growth = preda.ec_dmu(df_compare)
source_pc_machinery = preda.source_pc_sector(df, 242, 42, 23)
comparison = preda.comparison(df, 242, 42, 23)
source_pd_sector = preda.source_pd_sector(source_pc_machinery, comparison, 242, 42, 23)
avg_change_total = preda.average_change(df,'total')
avg_change_total.to_excel(writer, 'overall_avg_change')
writer.save()
preda.visualize_change_by_group(avg_change_total, 'total')
df_old = df.iloc[0:242,]
df_young = df.iloc[242:284,]
df_newborn = df.iloc[284:307,]
avg_change_by_age = preda.avg_change_bygroup(df_old, df_young, df_newborn)

preda.visualize_change_by_group(avg_change_by_age, 'newborn')
preda.visualize_change_by_group(avg_change_by_age, 'old')
preda.visualize_change_by_group(avg_change_by_age, 'young')

preda.visualize_change_by_component(avg_change_by_age,'MI')
preda.visualize_change_by_component(avg_change_by_age,'EC')
preda.visualize_change_by_component(avg_change_by_age,'TC')
예제 #2
0
preda.visualize_change_by_group(
    malm_change_chem, 'young',
    'The evolution in MI, EC, and TC during 2011-2018 of young firms in chemical sector'
)
preda.visualize_change_by_group(
    malm_change_chem, 'intermediate',
    'The evolution in MI, EC, and TC during 2011-2018 of intermediate firms in chemical sector'
)
preda.visualize_change_by_group(
    malm_change_chem, 'matured',
    'The evolution in MI, EC, and TC during 2011-2018 of matured firms in chemical sector'
)

preda.visualize_change_by_component(
    malm_change_chem, "MI",
    "Total factor productivity change of chemical sector (2010-2018)")
preda.visualize_change_by_component(malm_change_chem, "EC")
preda.visualize_change_by_component(malm_change_chem, "TC")

preda.visualize_change_by_group(
    malm_change_elec, 'young',
    'The evolution in MI, EC, and TC during 2011-2018 of young firms in electronic sector'
)
preda.visualize_change_by_group(
    malm_change_elec, 'intermediate',
    'The evolution in MI, EC, and TC during 2011-2018 of intermediate firms in electronic sector'
)
preda.visualize_change_by_group(
    malm_change_elec, 'matured',
    'The evolution in MI, EC, and TC during 2011-2018 of matured firms in electronic sector'