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Release Date :
Reference Number :
2019-8

La Union’s CPI posted at 112.9 in February 2019

The Consumer Price Index (CPI) in La Union in February 2019 was posted at 112.9.  This means that on the average, prices of goods and services in the province have increased by 12.9 percent from the base year 2012.  The province’s CPI was recorded at 112.8 in January 2019 and at 109.7 in February 2018. 

Meanwhile, Region I’s CPI was higher than La Union’s CPI in February 2018 and February 2019 which were posted at 113.1 and 118.3 respectively.

La Union inflation continues to ease in February 2019

Headline inflation in La Union further slowed down to 2.9 percent in February 2019.  The said rate was lower than by 0.4 percentage point as compared to the previous month which was recorded at 3.3 percent and 0.2 percentage point lower if compared to February of last year at 3.1 percent. 

The province's inflation rate stabilized from a high regime in 2018 (3.1 in February 2018) to as low as 2.5 in May 2018, went up to as high as 5.0 in August 2018. The inflation continued to climb in the following month of September 2018 until it reached the highest recorded inflation rate since 2013 of   6.7 percent in October 2018. Then the inflation started to stabilize to 6.2 percent and 4.7 percent in November and December, respectively. In February 2019, inflation further slide down to 2.9 percent.

Meanwhile, Region I’s headline inflation in February 2019 also further slowed down to 4.6 percent.  Inflation in the Ilocos Region a month ago was posted at 5.0 percent and 3.8 percent in February 2018.

From January 2019 to February 2019, faster pace of annual increases were posted in the indices of food and non-alcoholic beverages (5.0% to 5.1%); fruits            (1.1% to 1.7%); vegetables (12.8% to 16.0%); meat (2.8% to 3.0%); milk, cheese and eggs (0.9% to 2.4%); sugar, jam, honey, chocolate and confectionery increased (11.5% to 11.6%). Overall the province’s food alone index manifested a notch higher from 4.8 percent in January 2019 to 4.9 percent.

In the indices in housing, water, electricity, gas and other fuels; transport;             non-alcoholic beverages; rice; fish; and products not elsewhere classified annual gain in the province slowed down at 4.7% to 3.4%, 0.7% to -0.2%, 8.1% to 6.8%, 5.0% to 4.9%, 8.0% to 6.4%, and 3.3% to 0.4%, respectively.

Relative to their previous month’s annual rates, no change were noted in the indices of health at 1.6 percent, bread and cereals at 4.0 percent, both other cereals, flour, cereal preparation, bread, pasta and other bakery products at 0.9 percent, and oils and fats at 2.4 percent.

The major commodity group Food and Non-Alcoholic; Clothing and Footwear; increased at 5.0% to 5.1% and 1.4% to 1.7%, respectively. The following commodities remained at their previous month’s rates: Furnishings, Household Equipment and Routine Maintenance of the House at 3.6 percent; health at            1.6 percent; communication at 0.6 percent; recreation and culture at 1.9 percent; and education at -12.0 percent. However, Alcoholic Beverages and Tobacco; Housing, Water, Electricity, Gas and Other Fuels; Transport; and Restaurant and Miscellaneous Goods and Services decreased at 11.5% to 8.4%, 4.7% to 3.4%, 0.7% to -0.2%, and 1.0% to 0.9%, respectively.

PPP in La Union remains at PhP 0.87 in November 2018

 

The Purchasing Power of the Peso (PPP) in La Union was posted at PhP 0.89 in February 2019, the same figure as of last month. This means that the purchasing capability of PhP 1.00 in 2012 decreased by 11 centavos in February 2019.              La Union’s PPP was recorded at PhP 0.91 the same month a year ago.

From February2018, the PPP in the province was pegged at PhP 0.91 remained until the month of May 2018, decreased to PhP 0.90 in June 2018 and remained still in July 2018. It went down to PhP 0.88 in August 2018 and further went down to      PhP 0.87 in September 2018 and remained still until November 2018. The PPP in the province went up to PhP 0.88 in December 2018. It continued to go up to       PhP 0.89 in the month of January 2019 and remained still in the month of     February 2019.

La Union’s PPP in February 2019 was higher than Region I’s PPP of PhP 0.85.  The region’s PPP was posted at PhP 0.85 in January 2019 and at PhP 0.88 in     February 2018.

The Philippine Statistics Authority generates and announces the monthly Consumer Price Index (CPI) based on a nationwide survey of prices for a given basket of goods and services. 

The CPI  is an indicator of the change in the average retail prices of a fixed basket of goods and services commonly purchased by households relative to a base year.  It shows how much on the average, prices of goods and services have increased or decreased from a particular reference period known as base year.  It also serves as a basis for economic analysis, collective bargaining agreements, for wage adjustments, and for monitoring the effects of government economic policy on households. 

 

 

 

Rebasing of CPI to Base Year 2012 and Adopting the Chain Method in the 2012-based CPI

The Philippine Statistics Authority (PSA) released the Consumer Price Index (CPI) for All Income Households with base year 2012 on 06 March 2018.  The 2012-based CPI is the tenth in the rebasing series.  This was announced in press release number 2018-031 dated 22 February 2018.  Data users can expect two sets of the CPI as the new series shall be issued simultaneously with the 2006-based series until June 2018.  The CPI series for July 2018 onwards shall be 2012-based.

  1.  Identification of the Base Year  

The base period is the period, usually a year, at which the index number is set to 100.  It is the reference point of the index number series. The CPI is now rebased to 2012 base year from the current 2006 base year. 

The year 2012 was chosen as the next base year because it was the latest year when the Family Income and Expenditure Survey (FIES) results were made available.  It is also in accordance with PSA Board Resolution No. 1, Series of 2017-146, which approved the synchronized rebasing of the price indices to base year 2006 and every six (6) years thereafter. 

  1. Determination of the Market Basket 

Market basket refers to a sample of goods and services, which is meant to represent the totality of all goods and services purchased by households relative to a base year. 

Determining the right market basket is crucial because inadequate representation of the typical basket will give wrong signals as to the behavior of prices, a very important factor in economic planning. 

To determine the commodities that will form the market basket for the 2012-based CPI, the updating of the 2006 basket through the Survey of Key Informants was conducted from 07 October to 15 November 2013.  The survey was conducted nationwide to store managers, sellers or proprietors and were asked of the most commonly purchased items or commodities.  The commodities are grouped according to the 2010 Philippine Classification of Individual Consumption According to Purpose (COICOP) which is based on the United Nations COICOP. 

  1. Determination of the Household Consumption Patterns (Weights)

This activity involves assigning weights to the commodity groups/sub-groups.  This reflects the consumption priorities of households and the way they allocate resources to meet their needs.  Weight is a value attached to a commodity or group of commodities to indicate the relative importance of that commodity or group of commodities in the market basket. 

The weights for the 2012-based CPI were derived from the expenditure data of the 2012 FIES, a survey that covered around 50,000 sample households nationwide.  The weight for each item of expenditure is a proportion of that expenditure item to the total national expenditure.  The total (all items) national expenditure weights is equal to 100. 

The 2012 FIES expenditure data were used to directly estimate the 2012 CPI weights at the national and regional levels.  However, the 2012 FIES estimates for the expenditure data at the provincial level were not directly utilized in estimating the CPI expenditure weights as the data at the provincial/city level may not be reliable with the use of the households’ master sample (MS) that was utilized in selecting the 2012 FIES sample households.  The MS was drawn using regions as domains in generating estimates in all the household surveys of the PSA starting July 2003. 

The provincial/city expenditure data were derived using the model-based method in small area estimation procedures using the regional expenditure data as the control total for all the expenditure data within the specific region.  Using these estimates, the weight for each item of expenditure is computed as a proportion of that item of expenditure to the total national expenditure.  A raking procedure was done to adjust the weights of the provinces so that the provincial weights when added up will equal to the regional weights. 

  1. Monitoring of Prices of Items in the Market Basket

This involves establishing baseline information for prices of the items in the base year and monitoring the prices of the items on a regular basis.  Collection of data for the CPI is done by the provincial staff of the PSA.  Except for food, beverage and tobacco (FBT) in the National Capital Region(NCR) and petroleum products which are monitored on a weekly basis, price collection is generally done twice a month.  First collection phase is done in the first five days of the month while the second phase is on the 15th to 17th day of the month.  Data are collected from the sample outlets (outlets or establishments where prices of commodities/services are collected or quoted) which were chosen using the following criteria:

  1. Popularity of an establishment along the line of goods to be priced – this means the sample outlet is publicly noted in the locality for selling goods included in the CPI market basket and the outlet is patronized by a large segment of the population. 
  2. Consistency and completeness of stock

Consistency of stock – the outlet has a constant, steady or regular stock of commodities listed in the CPI price collection forms as well as of those commodities of the same kind and belonging to the same commodity group.

Completeness of stock – the sample outlet carries in its stock many if not all of the items included in the CPI price collection forms relative to the other outlets in the area. 

  1.  Permanency of outlet – the outlet is an established store or stall in the market area.  It should not be an ambulant or transient vendor in order that the collection of data can be done for the succeeding survey rounds. 
  2. Geographical location – the outlet is conveniently located and is accessible to the majority of consumers in the area. 

 

  1.  Computation of the CPI

The PSA employed the weighted arithmetic mean of price relatives and the “Chain” method to provide timely indicators since this method allows the inclusion or exclusion of commodities in the market basket to address the changing consumer taste and preferences and technological changes. Below are the steps in the computation of CPI using the 2012 as the base year:

Economic Indicators Derived from the CPI

Two important indicators, the inflation rate and purchasing power of the peso (PPP), are derived from the CPI which are important in monitoring price stability and the value of the country’s currency.

Inflation Rate is the annual rate of change or the year-on-year change of the CPI expressed in percent. The formula is:

Inflation Rate  =

Where:CPI2 – is the CPI in the second period

CPI1 – is the CPI in the previous period

Headline Inflation is the rate of change in the weighted average prices of all goods and services in the CPI basket while Core Inflation refers to the rate of change in the CPI that excludes the following item/commodity groups: rice, corn, fruits and vegetables, and fuel items.

The PPPmeasures the real value of the peso in a given period relative to a chosen reference period. It is computed by getting the reciprocal of the CPI and multiplying the result by 100.

PPP=

 

 

 

 

NIÑO E. TUAZON

(Supervising Statistical Specialist)

              Officer-in-Charge