Price Survey Results Report
Policy Department
April 2007
Published by the Labour Market Regulatory Authority
Kingdom of Bahrain
For Inquiries and Correspondence:
Policy Development Department or
Public Relations Department
Price Survey Monthly Report
Labour Market Regulatory Authority
PO Box 18333
Kingdom of Bahrain
Tel: 17388888
Working Team:
Policy Development Department Advisor
Dr. Farhad Mehran
Tel: 17388600
Email:
Data Collection & Research Director
Mr. Mona Hatem
Tel: 17388606
Email:
Survey Supervisor
Mr. Ashraf Hafez
Tel: 17388713
Email:
Survey Data Processor
Mrs. Rania Hubeishi
Tel: 17388911
Email:
Analysis and Report Writing
Miss Eman Al Sammak
Tel: 17388612
Email:
Price Survey Results Report
Introduction:
The LMRA’s Policy Development Department has undertaken conducting a simple survey to serve in alerting the changes in consumer prices in the Kingdom. This is part of the process of enforcing the provisions of Law No.(19) of 2006 with respect to the Regulation of the Labour Market in which Article 4-2 about LMRA’s Functions Jurisdictionsas follows: “To collate and analyze data and information and statistics related to the economic situation in the kingdom and in particular the Labour market, so that the Authority will be the principle source that releases the accurate intelligence and information and statistics related to the Labour market in the kingdom. The authority will update and manage this data and information continuously in order to represent the true picture of the economy in the kingdom. The Authority will prepare a report which will be published in the appropriate media to be determined by the Board in a manner that every one concerned has access to the reports.”[1] The provisions of Article 42-C of the Decree state: “The Authority prior to proposing any fees must take into consideration the rules and regulations set by this law, and that any change in the fees must be done pursuant to studies and commercial surveys with regards to the impact of these changes in fees on the GDP in the kingdom, in particular to that which pertains to inflation and the Consumer price Index.”[2] The above will be achieved through compiling data about the kinds and prices of goods of various sources and markets on a regular monthly basis.
This survey seeks to give a clear and simple picture of the changes in market prices and impact of the new policies in terms of rises and falls to sever as a basis for LMRA’s representatives in adopting new policies and decisions that may have positive or negative effects on the market. Indeed, it will help in investigating their relationship with the labour market policies; hence this survey will give a clear picture of the market conditions before and after applying the policies and will serve as an alarm bell in cases of steady and unjustifiable price increases.
This survey will serve as a base for a new index that has been developed by the Policy Development Department for measuring and providing alerts for changes in process. This index is called the Consumer Price Alert (or CPA). The index is designed to monitor and calculate change points in terms of price increases and declines to alert us about the overall situation of consumer prices whose components include the cost of foreign labour. It should be noted that the percentage of foreign labour is relatively high in certain sectors. The most important of these are the small industries sector in which foreign labour represents a very high percentage estimated at 91%, followed by the restaurant and hotel sector with 88%, contracting sector with 84% and the trade exchange sector with 76%[3].
This index is totally different from the Standard Consumer Price Index (Price Basket) which is followed by the Central Informatics Organization. It is also different from the regular monitoring of prices by the Ministry of. The Consumer Price Alert does not measure the inflation rate and it is not possible to measure through it. In addition, it is not based upon calculation of the Gross Domestic Product but it is only an alert index to investigate the reasons when the market is affected by the new policies introduced by LMRA, especially the control of the effect arising from the introduction of the new foreign labour fees upon consumer prices.
The difference between the Standard Consumer Price Index and the Consumer Price Alert lies in the fact that the latter depends upon a group of commodities that are likely to be influenced by the labour fees as they are often goods and products that heavily rely in providing them upon foreign manpower. It also differs in its calculation from the Standard Consumer Price Index as it does not depend upon calculating the weight of each commodity.
This survey was undertaken by specialists of the LMRA Policy Development Department and was closely monitored by LMRA analysts, statisticians, researchers and supervisors. We hope that this survey will achieve its objective and will provide useful and valuable information for the policy makers. It is hoped that it will give a clear picture from which we can get the special data and indicators required by analysts and researchers in their work to reflect positively upon the political and economic conditions in the Kingdom. We would like to seize this opportunity to express our thanks and appreciation to everyone who has co-operated with us in the data collection, classification, processing and analysis. The results of this survey are the fruit of the efforts made and the joint co-operation of the LMRA Policy Development Department team.
With the Grace of God,
Labour Market Regulatory Authority
Steps of collecting commodities prices data:
The price survey conducted by LMRA Policy Development Department takes a select basket of goods that include in their components foreign labour cost; hence their prices are likely to be affected by the labour market policies.
The survey covers 76 basic products selected with various specifications decided by LMRA so that their number totaled 113 products which are likely to be increased in the future and their choice will be on the basis of diversity, desired use and speed of their market trading. This takes place after asking about their basic sources and recording their information for future pricing. These products’ price data are compiled on the basis of the following 5 categories:
- Clothes
- Food and beverages
- Cleaning items
- Services
- Housing
As part of this operation, a surveyor regularly distributes the goods over the days of the last week of each month and the first week only of the new month, which is the familiar shopping period in the Kingdom. Prices of certain goods are monitored during the weekly holiday such as fruit and vegetables and their price is computed once in every month (On the basis of the weekly holiday). Then, a surveyor visits the sources and markets of the selected group of goods and inquires about the basic prices of each. The data are directly entered in the survey form in which prices are shown according to the names of such goods, date of the visit, item, kind and the source name. Of course, the basic and normal prices are the ones being calculated not the special offer prices.
When a surveyor is unable to obtain the data for any of the goods, the data will be considered missing. The missing information is usually divided into three sections, temporarily missing data, seasonally missing data or permanently missing data. Such data are dealt with on the basis of either replacement or elimination. If the data about a certain commodity is permanently missing, the surveyor will have one of two options, either to replace the commodity by another similar one while taking the details of the other commodity in the current and previous months or to delete the commodity from the survey, hence the data processor will do the needful. If the commodity’s data are temporarily missing, they are changed by changing the source by the surveyor and the previous source will be deleted by the data processor. However, if the commodity’s data are seasonally missing, the survey will continue normally with calculation of the data for the last month without making any changes until the commodity becomes available in the market.
Defining the nature of the missing data as to whether they are temporary, seasonal or permanent is usually on the basis of considering the commodity missing on a seasonal basis if it is not available in all the sources. For a number of indicators it may be considered missing temporarily when the commodity appears once again and its loss is not on a temporary and clear basis. Finally, the commodity will be considered temporarily missing when it continued to be unavailable for a very long period of time with no hope of its return to the market.
For the collection of prices, 84 sources or supermarkets are used with a condition of at least 3 sources for each commodity and some of them having 5 sources. Such sources are based upon their popularity and the customers who usually buy from them taking into account the locations of such sources and their presence throughout the Kingdom. Other factors include accessibility to such locations from the surrounding villages, how fast they are influenced by market policies and how remote they are from the authorities’ control. Such sources varied according to their specialties, types and locations.
Data Processing:
Following the collection of the comodities data in the questionnaire print outs, the data are processed by entering them under a new label in the computer, which is designed and programmed for this study. All the details obtained about the commodity have been coded and a manual of such digital codes has been prepared for identifying the goods and classifying the different items or their sources, in addition to codes for distinguishing the country of origin and measurement units.
The questionnaire has been designed by Microsoft Access to complete the data entry manually from the questionnaire printouts to the electronic forms on the computer. The electronic questionnaire contains all the surveyed comodities with their different sources. The person who enters the data has to key in the price and date of making the computer entry.
The electronic questionnaire file is saved each time by a label containing the month and year in which the questionnaire data are obtain. Thus, reference to the electronic questionnaire and its data becomes easy through an access to the file that carries the label of the required month and year.
Following the manual copying and saving the data manually, such data is analyzed by comparison and computing the required differences and indicators; the most important of which is the “Consumer Price Alert”. The calculation takes place with the use of the same software “Microsoft Access” which is used from the beginning for the processing of this survey. Microsoft Access contains the database and it is designed in such a way to enable the analyst to use the data in his analysis. For observing the results, the program “Microsoft Access” has the ability to achieve this target by programming it internally.
Revising the data and ensuring that they are correct take place by printing several reports designed in the program to be easily prepared and by a press of a button. Such reports give a summary of the date for each survey in terms of number, type and date and according to the item and source. In addition, there is a special report that gives a detailed description of the commodities whose prices have increased or fell with alert colors[4] being shown in case of increase or reduction through which comparison can be made and the elements of error can be identified, especially if the change is illogical. At this point, reference will be made to the data compiler to ensure the correctness of the data in the questionnaire and to reduce the rate of error as far as possible. On the other hand, there is another report that can be prepared to show the missing data which through it one can find the reason why such data is missing from the data compiler.
Approach to Calculation of the CPA Index:
CPA Index=
Whereas:
N = Actual total number of goods
N+ = Number of goods whose prices rose.
N- = Number of goods whose prices fell.
The calculation process is done through calculating the actual total number of goods included in the survey so that all the information concerning the commodity, especially the price, is obtained. N stands for the actual total number of goods. Then, prices of such goods are classified according to the rate of increase or decrease in the price. Accordingly, the number of commodities whose prices rose is shown as N +. The goods whose prices fell are coded as N-.
Then, the difference is found between the number of goods whose prices rose (N+) and the number of goods whose prices fell (N-), and subsequently the result is divided by the actual total number of goods (N). At this point, the result will be in fractions that are multiplied by (100) to obtain the percentage point of the CPA index, which means a significant total increase in prices when it is positive and a decline when it is negative; and stable when it equals nil. After obtaining the value of CPA Index, the result will be compared against the Sigma mean () through which can be identified the kind of price increase or decline and whether it is significant, slight or stable.
The Sigma coefficient () is the standard deviation of the CPA Index when prices change randomly with a probability of 5%, whether the price change is positive or negative.
Goods Subject to Price Monitoring According to Classification
Clothes / Cleaning ItemsArabian perfumes
Men’s Thoab tailoring
Women’s Abaya tailoring
Jeans / Facial Tissue
Dishwashing liquid
Toothpaste
Hair shampoo
Body soap
Food and Beverages / Services
Sheep meat
Beef
Fresh chicken
Bananas
Apples
Lettuce
Tomatoes
Potatoes
Barbeer
Radish
Onions
Nescafe
Arabian Coffee
Tea
Canned fruit juice
Mineral water
Eggs
Powder milk
Fresh milk
Bread
Rice
Cornflakes
White sugar
Potato chips
Pufak (corn crisps)
Cake
Tomato paste
Sunflower oil
Beef burger sandwiches
Pizza, medium size
Humus with bread
Soup of the day
Chello Kabab
Ice cream
Hubble-bubble (Shisha)
Cigarettes
Panadol / Auto Maintenance- Oil changing w/filter
Auto Maintenance- Breaks Fixing
Auto Maintenance- Tyre Changes
Auto Maintenance- Wheel Alignment
Laundry Dry cleaning
Laundry Washing
Private school fees
Health care
Men’s hair cut
Beauty Care
Movies
Gym membership
Housing
Wash basin set
Bathroom set
Bidet set
Tiles
Wood
Mattress- Single
Mattress- Double
Cement
Ready-mix concrete (35 Newton)
Blocks (8”)
Sand
Precast
Air conditioners servicing
Labour (free visa) charges
Painting charges
Fitting kitchens and bathrooms
Monthly apartment rent
Electricity
Water
* the commodities mentioned in the table above are the main commodities where its real number exceeding the mentioned ones depending on the different groups and classifications.
Price Survey Results Tables
Goods in General / CPA / N / +N / -N / Balance / / ColorMonth/ Year
2006-12 / 7PTS / 231 / 23 / 6 / 202 / 2% /
2007-01 / 0 PTS / 226 / 12 / 11 / 203 / 2% /
2007-02 / -1 PTS / 210 / 48 / 51 / 111 / 2% /
2007-03 / 0 PTS / 210 / 33 / 34 / 143 / 2% /
2007-04 / 6 PTS / 282 / 24 / 7 / 251 / 2% /
2007-05 / 3 PTS / 318 / 11 / 3 / 304 / 2% /
Imported Goods /
CPA
/ N / +N / -N / Balance / / ColorMonth/
Year
2006-12 / 12 PTS / 146 / 21 / 3 / 122 / 3% /
2007-01 / -1 PTS / 141 / 10 / 11 / 120 / 3% /
2007-02 / -8 PTS / 135 / 29 / 40 / 66 / 3% /
2007-03 / 0 PTS / 135 / 24 / 24 / 87 / 3% /
2007-04 / 7 PTS / 136 / 15 / 5 / 116 / 3% /
2007-05 / 1 PTS / 163 / 5 / 3 / 155 / 2% /
Local Goods / CPA / N / +N / -N / Balance / / Color
Month/ Year
2006-12 / 0PTS / 48 / 2 / 2 / 44 / 5% /
2007-01 / 4 PTS / 48 / 2 / 0 / 46 / 5% /
2007-02 / 7 PTS / 45 / 10 / 7 / 28 / 5% /
2007-03 / 2 PTS / 45 / 6 / 5 / 34 / 5% /
2007-04 / -2 PTS / 61 / 1 / 2 / 58 / 4% /
2007-05 / 3 PTS / 67 / 2 / 0 / 65 / 4% /
Foods & Beverages / CPA / N / +N / -N / Balance / / Color
Month/ Year
2006-12 / 12 PTS / 165 / 23 / 3 / 139 / 2% /
2007-01 / 1 PTS / 160 / 12 / 11 / 137 / 3% /
2007-02 / -4 PTS / 153 / 34 / 40 / 79 / 3% /
2007-03 / 1 PTS / 153 / 28 / 26 / 99 / 3% /
2007-04 / 4 PTS / 165 / 13 / 6 / 146 / 2% /
2007-05 / 2 PTS / 193 / 6 / 3 / 184 / 2% /
Imported Foods & Beverages / CPA / N / +N / -N / Balance / / Color
Month/ Year
2006-12 / 15 PTS / 122 / 21 / 3 / 98 / 3% /
2007-01 / -1 PTS / 117 / 10 / 11 / 96 / 3% /
2007-02 / -7 PTS / 112 / 25 / 33 / 54 / 3% /
2007-03 / 1 PTS / 113 / 22 / 21 / 70 / 3% /
2007-04 / 7 PTS / 108 / 12 / 4 / 92 / 3% /
2007-05 / 1 PTS / 131 / 4 / 3 / 124 / 3% /
Local Foods & Beverages / CPA / N / +N / -N / Balance / / Color
Month/ Year
2006-12 / 5 PTS / 43 / 2 / 0 / 41 / 5% /
2007-01 / 5 PTS / 43 / 2 / 0 / 41 / 5% /
2007-02 / 5 PTS / 41 / 9 / 7 / 25 / 5% /
2007-03 / 3 PTS / 40 / 6 / 5 / 29 / 5% /
2007-04 / -2 PTS / 57 / 1 / 2 / 54 / 4% /
2007-05 / 3 PTS / 62 / 2 / 0 / 60 / 4% /
Other Goods / CPA / N / +N / -N / Balance / / Color
Month/Year
2006-12 / -5 PTS / 43 / 0 / 2 / 41 / 5% /
2007-01 / 0 PTS / 43 / 0 / 0 / 43 / 5% /
2007-02 / 0 PTS / 39 / 7 / 7 / 25 / 5% /
2007-03 / -3 PTS / 39 / 2 / 3 / 34 / 5% /
2007-04 / 7 PTS / 73 / 6 / 1 / 66 / 4% /
2007-05 / 3 PTS / 78 / 2 / 0 / 76 / 4% /
Other Imported Goods / CPA / N / +N / -N / Balance / / Color
Month/Year
2006-12 / 0 PTS / 24 / 0 / 0 / 24 / 6% /
2007-01 / 0 PTS / 24 / 0 / 0 / 24 / 6% /
2007-02 / -13 PTS / 23 / 4 / 7 / 12 / 7% /
2007-03 / -5 PTS / 22 / 2 / 3 / 17 / 7% /
2007-04 / 7 PTS / 28 / 3 / 1 / 24 / 6% /
2007-05 / 3 PTS / 32 / 1 / 0 / 31 / 6% /
Other Local Goods / CPA / N / +N / -N / Balance / / Color
Month/Year
2006-12 / -40 PTS / 5 / 0 / 2 / 3 / 14% /
2007-01 / 0 PTS / 5 / 0 / 0 / 5 / 14% /
2007-02 / 25 PTS / 4 / 1 / 0 / 3 / 16% /
2007-03 / 0 PTS / 5 / 0 / 0 / 5 / 14% /
2007-04 / 0 PTS / 4 / 0 / 0 / 4 / 16% /
2007-05 / 0 PTS / 5 / 0 / 0 / 5 / 14% /
Housing / CPA / N / +N / -N / Balance / / Color
Month/Year
2006-12 / -4 PTS / 23 / 0 / 1 / 22 / 7% /
2007-01 / 0 PTS / 23 / 0 / 0 / 23 / 7% /
2007-02 / 40 PTS / 25 / 14 / 4 / 7 / 6% /
2007-03 / 5 PTS / 21 / 6 / 5 / 10 / 7% /
2007-04 / 22 PTS / 50 / 11 / 0 / 39 / 4% /
2007-05 / 10 PTS / 49 / 5 / 0 / 44 / 5% /
Color Keys
/ CPA < - / - <= CPA < +
/ + <= CPA < 2*
/ 2* <= CPA
Results of analysis and charts are subject to the results of the above Tables.
Red = Significant rise/ Yellow = Slight rise/ Green = Stable/ Blue = Significant fall.
Analysis and Recommendations:
The survey results show that the prices of goods were affected by variables compared with the months during which the survey was conducted (From November 2006 to May 2007).
Prices were compared after classifying the goods as to whether they were imported goods or locally made ones. In general, figures showed that there was a significant price increase in December to the point that the prices of imported goods increased by 12 percentage points compared to their earlier levels, hence scoring a minor effect on local goods whose prices rose marginally and such effect only appeared two months later, i.e. in February 2007, which scored a significant rise in prices of imported goods. The following Chart shows the reality of the rise in prices of imported consumer goods that affected in general the prices of goods and cause a significant increase in price levels.