Naïve Forecasts

Forecast for the one month ahead horizon is the same as that for the 12 months ahead horizon as the data are seasonal.

3.9.1 Naïve forecast of arrivals from all countries

Table 3.9.1 shows the naive forecasting performance for tourist arrivals to Japan from all countries. For the one-year lead period the forecasting performance is good (MAPE less than 10%) for the 12 months ahead and 24 months ahead forecasting horizons. For the two-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for both horizons. The RMSE figures are consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.1 Naive Forecasting Performance

for Tourist Arrivals to Japan from All Countries

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 47084 9.92 47084 9.92 43323 9.26

2 year 59512 12.30 59512 12.30 66744 13.93

3.9.2 Naïve forecast of arrivals from Australia

Table 3.9.2 shows the naive forecasting performance for tourist arrivals to Japan from Australia. For the one-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months ahead and 24 months ahead forecasting horizons. For the two-year lead period the forecasting performance is good (MAPE

Chapter 4 ARIMA and BSM Forecasting 112

less than 10%) for the 12 months ahead horizon and fair (MAPE between 10% and 20%) for the 24 months ahead horizon. The RMSE figures are consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.2 Naive Forecasting Performance

for Tourist Arrivals to Japan from Australia

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 1455 10.07 1455 10.07 1748 10.80

2 year 1351 8.62 1351 8.62 2087 13.02

3.9.3 Naïve forecast of arrivals from Canada

Table 3.9.3 shows the naive forecasting performance for tourist arrivals to Japan from Canada. For the one-year lead period the forecasting performance is good (MAPE less than 10%) for the 12 months ahead horizon and fair (MAPE between 10% and 20%) for the 24 months ahead horizon. For the two-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months ahead and 24 months ahead forecasting horizons. The RMSE figures are consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.3 Naive Forecasting Performance

for Tourist Arrivals to Japan from Canada

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 1120 8.60 1120 8.60 1372 10.37

3.9.4 Naïve forecast of arrivals from China

Table 3.9.4 shows the naive forecasting performance for tourist arrivals to Japan from China. For the one-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months ahead horizon and poor (MAPE 20% or more) for the 24 months ahead horizon. For the two-year lead period the forecasting performance is poor (MAPE 20% or more) for both horizons. The RMSE figures are fairly consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are poor.

Table 3.9.4 Naive Forecasting Performance for Tourist Arrivals to Japan from China

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 5887 14.21 5887 14.21 9318 21.00

2 year 8476 27.30 8476 27.30 10954 32.48

3.9.5 Naïve forecast of arrivals from France

Table 3.9.5 shows the naive forecasting performance for tourist arrivals to Japan from Canada. For the one-year lead period the forecasting performance is good (MAPE less than 10%) for the 12 months ahead horizon and fair (MAPE between 10% and 20%) for the 24 months ahead horizon. For the two-year lead period, the forecasting performance is also good (MAPE less than 10%) for the 12 months ahead horizon and fair (MAPE between 10% and 20%) for the 24 months ahead horizon. The RMSE figures are consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Chapter 4 ARIMA and BSM Forecasting 114

Table 3.9.5 Naive Forecasting Performance

for Tourist Arrivals to Japan from France

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 585 6.34 585 6.34 940 11.93

2 year 852 9.40 852 9.40 889 10.65

3.9.6 Naïve forecast of arrivals from Germany

Table 3.9.6 shows the naive forecasting performance for tourist arrivals to Japan from Germany. For the one-year lead period the forecasting performance is good (MAPE less than 10%) for the 12 months-ahead horizon and fair (MAPE between 10% and 20%) for the 24 months ahead horizon. For the two-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for both horizons. The RMSE figures are fairly consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.6 Naive Forecasting Performance

for Tourist Arrivals to Japan from Germany

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 1092 7.87 1092 7.87 1317 10.30

2 year 1247 11.20 1247 11.20 1268 10.97

3.9.7 Naïve forecast of arrivals from Korea

Table 3.9.7 shows the naive forecasting performance for tourist arrivals to Japan from Korea. For the one-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months ahead and 24 months ahead forecasting horizons. For the two-year lead period, the forecasting performance is also fair (MAPE between 10% and 20%) for both horizons. The RMSE figures are consistent

with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.7 Naive Forecasting Performance for Tourist Arrivals to Japan from Korea

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 13113 10.51 13113 10.51 18600 15.90

2 year 17606 12.75 17606 12.75 26280 18.34

3.9.8 Naïve forecast of arrivals from Singapore

Table 3.9.8 shows the naive forecasting performance for tourist arrivals to Japan from Singapore. For the one-year lead period the forecasting performance is poor (MAPE 20% or more) for the 12 months-ahead horizon and good (MAPE less than 10%) for the 24 months ahead horizon. For the two-year lead period the forecasting performance is poor (MAPE 20% or more) for both horizons. The RMSE figures are consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are poor.

Table 3.9.8 Naive Forecasting Performance

for Tourist Arrivals to Japan from Singapore

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 1644 21.34 1644 21.34 993 9.09

Chapter 4 ARIMA and BSM Forecasting 116

3.9.9 Naïve forecast of arrivals from Taiwan

Table 3.9.9 shows the naive forecasting performance for tourist arrivals to Japan from Taiwan. For the one-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months ahead and 24 months ahead forecasting horizons. For the two-year lead period, the forecasting performance is also poor (MAPE 20% or more) for both horizons. The RMSE figures are fairly consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 24 months ahead forecasting horizon but poor for the 2-year lead period.

Table 3.9.9 Naive Forecasting Performance

for Tourist Arrivals to Japan from Taiwan

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 12620 14.17 12620 14.17 9149 10.55

2 year 19842 35.43 19842 35.43 20045 34.39

3.9.10 Naïve forecast of arrivals from the UK

Table 3.9.10 shows the naive forecasting performance for tourist arrivals to Japan from the UK. For the one-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months-ahead horizon and poor (MAPE 20% or more) for the 24 months ahead horizon. For the two-year lead period, the forecasting performance is also fair (MAPE between 10% and 20%) for the 12 months ahead horizon and poor (MAPE 20% or more) for the 24 months ahead horizon. The RMSE figures are fairly consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 12 months ahead forecasting horizon.

Table 3.9.10 Naive Forecasting Performance

for Tourist Arrivals to Japan from the UK

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 3815 12.72 3815 12.72 14877 79.46

2 year 3817 13.50 3817 13.50 10569 43.31

3.9.11 Naïve forecast of arrivals from the USA

Table 3.9.11 shows the naive forecasting performance for tourist arrivals to Japan from the USA. For the one-year lead period the forecasting performance is good (MAPE less than 10%) for the 12 months ahead and 24 months ahead forecasting horizons. For the two-year lead period the forecasting performance is fair (MAPE between 10% and 20%) for the 12 months-ahead horizon and good (MAPE less than 10%) for the 24 months ahead horizon. The RMSE figures are fairly consistent with the MAPE figures. Overall, the forecasting error increases with an increase in the lead period, and the model forecasts are most accurate over the 24 months ahead forecasting horizon.

Table 3.9.11 Naive Forecasting Performance

for Tourist Arrivals to Japan from the USA

Horizon One month ahead 12 months ahead 24 months ahead

Lead RMSE MAPE RMSE MAPE RMSE MAPE

1 year 6382 7.97 6382 7.97 2586 2.89

Chapter 4 ARIMA and BSM Forecasting 118