Irish Residential Property Price Index

This blog is the introduction to the Property Price Index that I am building for the final project of the Higher Diploma in Science – Data Science and Analytic in CIT. Next blogs will explain the data analysis performed and the model created.

Irish Residential Property Background

In the last four years, Residential Property and Property Prices has capture the attention of media and researchers alike in Ireland. The interest on this subject has increased at the same time that the Irish Property Bubble busted in 2010 (Pope, 2015) (Taylor, 2015) (Burke-Kennedy, 2015) (Newenham, 2015) (Hancock, 2014) (McKinley, 2013). From 1990’s to 2007 (Celtic Tiger Period), the number of real estate purchased increased due a positive growing economy. Rapid growth in Ireland was achieved by export-led growth with moderate wage and price inflation and healthy public finances (Honohan, 2009). The positive economy environment created a property bubble where prices increased quickly until 2007 (Gerard Kennedy, 2011). After this year with the financial crisis property prices and approved loans start falling until 2010.  This created unemployment within the construction sector. Property Market is a key element for the Irish economy (Conniffee & Duffy, 1999) (Kenny, 2015) and its relation with the financial sector impacts positively or negatively on the wealth of any household.

Houses sold in Ireland 2010 to 2014

Since early 2013 the prices are increasing again and number of houses purchased as well (Duncan, 2014) (Weston & Sheahan, 2014) (Brophy, 2014). The price evolution and its effect in the economy highlight the importance of property price models.

The importance of Property Price Model

Price (or market value) indices for property markets are important for the following reasons:

  • Individual Benchmarks purposes: property owners and investors can compare average returns on property and other assets such as stocks and bonds. It is an input into an individual citizen’s decision making on whether to buy (or sell) a residential property. Residential properties are seen as a profitable activity (renting, fix house and sell…).(Netzell, 2012) (Eurostats, 2013)
  • International Benchmarks purposes: It allows comparing the economy between different countries. It is used in making inter-area and international comparisons.. Residential Stock is part of the wealth of a country and property price index allow to quantify the value of this. (Eurostats, 2013)
  • Research on property markets and residential construction. Research topics where price indices are used include property cycles and the relationship between property markets and other financial markets. It is input into estimating the value of housing as a component of wealth (Netzell, 2012)(OECD, 2000) (Eurostats, 2013).
  • Allows forecasting the potential future private consumption: House prices affect the wealth position of households and household borrowing. Higher prices reduce the spent of buyers in order to save more to purchase the desired house. It is input into the consumer price index, which in turn is used for wage bargaining and indexation purposes. (Gerard Kennedy, 2011)(OECD, 2000) (CSO, 2015) (Eurostats, 2013).
  • Macro-economic indicator of economic growth: property prices can be useful indicators of demand pressures in the economy and business cycles. There is a positive correlation between economy expansion and rising house pricing (OECD, 2000)(Eurostats, 2013) (Plosser, 2007). For example, Bracke (2011) analyses House cycle and compare them with financial information including Real GDP, interest and inflation rates. (Bracke, 2011)
  • Economic and monetary/financial policy makers’ decisions. It is a measure for financial stability, risk evaluation, borrowing capacity, debt burden and aggregate consumption(Eurostats, 2013)(Plosser, 2007)



Bracke, P. (2011). How Long Do Housing Cycles Last? A Duration Analysis for 19 OECD Countries. Research Department . International Monetary Fund. Retrieved February 25, 2015, from

Brophy, D. (2014, July 24). Taoiseach on Dublin house prices: “I don’t accept there’s a bubble”. Retrieved February 26, 2015, from The Journal:

Burke-Kennedy, E. (2015, January 28). Property price inflation to moderate significantly – report. Retrieved February 20, 2015, from The Irish Times:

Conniffee, D., & Duffy, D. (1999, October). Irish House Price Indices —Methodological Issues*. The Economic and Social Review, Volume 30(No. 4), pp. 403-423. Retrieved February 20, 2015, from

CSO. (2015, February 22). Statistical Product – Consumer Prices Annual Series. Retrieved February 26, 2015, from Central Statistical Office:

Duncan, P. (2014, November 26). Dublin property prices 24% higher in a year. Retrieved February 26, 2015, from The Irish Times:

Eurostats. (2013). Handbook on Residential Property Prices Indices (RPPIs). Economy and finance. Luxembourg: Publications Office of the European Union. doi:10.2785/34007

Gerard Kennedy, K. M. (2011). Scenarios for Irish House Prices. Central Bank of Ireland.

Hancock, C. (2014, October 7). New mortgage rules mean most buyers to need 20% deposit. Retrieved February 20, 2015, from The Irish Times:

Honohan, P. (2009). WHAT WENT WRONG IN IRELAND? Dublin: Trinity College Dublin.

Kenny, E. (2015, February 19). Interview with An Taoiseach Enda Kenny. (R. News, Interviewer)

McKinley, C. (2013, July 24). Dublin house prices increase 7.7%. Retrieved February 20, 2015, from The Irish Times:

Netzell, O. (2012). A method for combining transaction- and valuation-based data in a property price index. Royal Institute of Technology, Building and Real Estate Economics, Stockholm. Retrieved February 23, 2015, from!/Menu/general/column-content/attachment/A%20method%20for%20property%20price%20index%20construction3b.pdf

Newenham, P. (2015, February 5). S&P: Ireland to see strongest rise in house prices in Europe. Retrieved February 20, 2015, from The Irish Times:

OECD. (2000). HOUSE PRICES AND ECONOMIC ACTIVITY. OECD Economic Outlook, Volume: 68, 169-184. Retrieved February 26, 2015, from

Plosser, C. I. (2007, July 11). House Prices and Monetary Policy. Retrieved February 26, 2015, from Federal Reserve Bank of Philadelphia:

Pope, C. (2015, February 25). Property prices suffer biggest monthly fall in three years. Retrieved February 2015, 2015, from The Irish Times:

Taylor, C. (2015, January 28). Property prices in Dublin up 23% in year to December. Retrieved February 26, 2015, from The Irish Times:

Weston, C., & Sheahan, F. (2014, July 25). Kenny denies bubble despite record surge in the price of homes. Retrieved February 26, 2015, from Independent:



Principal Components Analysis in R

Principal Components are really useful for dataset with a large number of variables that potentially are correlated between them. By creating vectors using the variables, we reduce the number of ‘variables’ to be included in the model. The aim is to include the components that explain the larger volume of variation of the dataset.

How to do Principal Components Analysis using R?

Initially, we need data so let’s go to create:

x1<- c(122, 21, 105, 101, 155, 131, 115, 53, 75, 45)
x2<-c(117, 32, 140, 105, 149, 146, 82, 60, 82, 37)

The we will scale it with:

Read more

VBA Create a Parabola

Excel allows creating programs using VBA (Visual Basic Applications).

This program shows how to create a parabola witb VBA:

Private Sub CmdBotton_Click()
Dim dblB As Double
Dim dblH As Double

‘User introduce values
dblB = InputBox(“please introduce a value for Base”, “Base Value”)
dblH = InputBox(“please introduce a value for Height”, “Height Value”)

‘Output value to Excel sheet
Range(“D17”).Value = dblH
Range(“D16”).Value = dblB

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Sentiment Analysis, Twitter and R

Within the Data Science and Analytic Higher Diploma, I have been asked:

“Research an area of sentiment analysis that is of interest to you. Describe the process that is required to implement the analysis and how you would do this.”

So I through myself to research using ‘Google’ some information about Sentiment Analysis and I found this Youtube video that explains how to use R and Twitter to do some Sentiment Analysis.

Personally I think Michael Herman did a fair job with this video; however, it was published on 2012 – therefore with different changes going on in Youtube and new R versions, the code provided show various errors.

So, after playing around with the code provided in the video and doing some searches I successfully analysed some data.

Here is my R code for the Sentiment Analysis proposed by Michael: Read more