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Table 3 Summary statistics for equation 3 * comparing 56 municipalities in Tokyo and 54 municipalities in North Rhine-Westphalia (NRW)

From: Impact of a fixed price system on the supply of institutional long-term care: a comparative study of Japanese and German metropolitan areas

Variables IF in Tokyo IF in NRW
  Mean (Standard deviation) Mean (Standard deviation)
Dependent variables     
Change in bed-densitya -0.95 (9.56) -0.64 (5.89)
Explanatory variables     
Costs/cost relevant     
Average size of new facilities (beds) 95.54 (26.98) 89.7 (67.55)
LTA land price for T (¥1000 s)/LTA rent-level for N 341.03 (285.98) 3.11 (1.02)
LTA wage of elderly care nurse for T (¥1000 s)/LTA duration for care nurse search for Nb (days) 205.05 (8.92) 54.3 (15.08)
Need     
LTA percent elderlyc needing LTC 15.70 (1.94) 14.5 (1.87)
LTA growth rate of elderlyc needing LTC 7.01 (2.21) 2.89 (5.24)
Profit/political intervention (control variables)     
Initial bed-densitya of IF 32.21 (43.59) 48.3 (8.79)
LTA bed-densitya of PNH 3.95 (4.11) - -
Densitya of subsidized beds 1.45 (2.94) - -
Demand (control variables)     
LTA percent elderlyc 18.12 (4.46) 18 (1.50)
LTA growth rate of elderlyc 4.16 (1.95) 2.04 (0.76)
LTA residential tax for T (¥1000 s)/LTA disposable income for N (€1000 s) 117.63 (64.52) 17.7 (1.72)
N 46-56   50-54  
  1. aBed density: number of beds per 1000 elderly adults aged 65 years and over.
  2. bVacancy duration for search of skilled care: time taken for an employer to find a skilled elderly care nurse.
  3. cElderly persons: those aged 65 years and over.
  4. *Equation 3. Supply under LTCI: ΔBDi = βBDi0 + βXi + βYi + βZi + α + e. ΔBid: change in bed density between the year shortly after LTCI introduction and the recent year in municipality i; BDi0: bed-density shortly before introducing LTCI in municipality i; β: coefficients; α: constant; e: error with zero mean; X: variables for costs; Y: variables for need; Z: control variables.