PAT Introduction to Graphical Analysis Session 2.1. WFP Markets Learning Programme2.1.1 Price Analysis Training

Learning Objectives By the end of this session, participants should be able to:  Describe the advantages of different types of graphs and charts and which is best used with particular types of data  Scale graphs in accordance with units used, and explain the meaning and intent of each of the axes on a graph  Identify the trends (dispersion, volatility, increasing/ decreasing) depicted by a graph  Identify the breaks in a data series and explain whether they are real or indicate problems with the data  Explain how to deal with missing data WFP Markets Learning Programme Price Analysis Training 2.1.2

Graphical Analysis: Why? “One picture is worth a thousand words.” Graphs:  can portray much valuable information  useful tools for summarizing data  are efficient means of communicating numerical info Research shows people retain info presented in graphs more than the same info written as prose WFP Markets Learning Programme Price Analysis Training 2.1.3

Exercise 2.1.a. Charts and Graphs – Strengths & Limitations Analyse the charts assigned to your team and discuss: 1. What types of data are being presented (e.g. discrete events or trends)? 2. What are the main messages the chart is trying to communicate to senior management? 3. What are the chart’s strengths/weaknesses in communicating these data/messages? 4. What recommendations can you make for improving presentation of this information? WFP Markets Learning Programme Price Analysis Training 2.1.4

Debriefing  Review charts in order: 1, 2, 3…etc. Data types? Messages? Strengths/weaknesses? Recommendations? WFP Markets Learning Programme Price Analysis Training What lessons have you learned from this exercise? What will you do differently in the future?

Strengths of Graphical Analysis  Visual rather than numeric: provides for relatively clear communication of complex phenomena  With Excel charts: easy to visualize effects of changes in quantities of particular variables  Previously unseen patterns – e.g., seasonal price patterns – can emerge and help with (cautious!) forecasting WFP Markets Learning Programme Price Analysis Training 2.1.6

Limitations: Graphical analysis…  Graphical analysis shows relationship between prices but does not quantify degree of this relationship  Graphical analysis doesn’t give clear understanding of direction of relationship (i.e. direction of price transmission)  Apparent relationship between prices on a graph (convergence, divergence) does not necessarily indicate meaningful relationship between them WFP Markets Learning Programme Price Analysis Training 2.1.7

Limitations: Graphical analysis…  Co-movement of price series in different locations at same time could be due to common factors affecting prices – e.g., seasonality, inflation, drought, war, prohibition, trade barriers – rather than to meaningful causal relationship in trade between the different locations  Interpretation of graph may need additional info: relationship between variables (prices) could be lagged, instantaneous, linear, non- linear, symmetric, or asymmetric WFP Markets Learning Programme Price Analysis Training 2.1.8

Example: “Other Factors” WFP Markets Learning Programme Price Analysis Training Jan 05Ban on private trade in grain (revive state dist system) 2. Jul 06 Floods 3. Jan 06Nuclear test, UN sanctions imposed 4. Apr 07Trading restrictions imposed 5. Aug 07Floods 6. Dec 07Chinese export controls, NK trading activity ban 7. Apr 08Trading activity controls tightened 8. May 08Military stocks reportedly ordered released May 08US aid announcement 9. Jun 081st US aid arrives at Nampo (1) 2006 (2) (3) 2007 (4) (5) (6) 2008 (7) (8) (9) Price index North Korean Grain Prices

The key messages… Use caution in extrapolating from price series! Know the underlying conditions / factors WFP Markets Learning Programme Price Analysis Training

Sample Price Analysis Graph: Increasing/Decreasing Trends WFP Markets Learning Programme Price Analysis Training Real millet prices in regions of Niger,

Sample Price Analysis Graph: Increasing/Decreasing Trends WFP Markets Learning Programme Price Analysis Training

Sample Price Analysis Graph: Dispersion WFP Markets Learning Programme Price Analysis Training Corn Rice Coefficient Coefficient of variation of grain prices across provinces,

Sample Price Analysis Graph: Volatility WFP Markets Learning Programme Price Analysis Training Volatility of average national sorghum prices across time

Charting with Excel: Points to ponder Choice of chart type & orientation: Keep it simple! Data labels & markers “Appropriate imprecision” Make the data table available for complex graph (as annex) What about missing data…? WFP Markets Learning Programme Price Analysis Training %? or 3.09% or 3.1%? or 3% ? ? 6 7 ? 9 ? ? 15 ? 17

Dealing with Missing Data Do nothing: Delete missing data records Data Imputation:  Mean substitution: Replace missing value with mean value (of previous and subsequent data values) for that particular attribute  Case Substitution: Replace missing value with historical value from similar cases. (We can not use value from current sample for case substitution; it must be from previous observations.) WFP Markets Learning Programme Price Analysis Training

Questions about using Excel? WFP Markets Learning Programme Price Analysis Training

Exercise 2.1.b. The Marketastan File: Excel Charts for Senior Managers  Aim of the exercise: Learning to communicate clearly to senior managers  Turn to Workbook Exercise 2.1.b.  Read the statements and then, with your partner, using Excel file (“2.1. b. Charts for WFP- Marketastan Senior Managers – Excel File.xls”), create a chart/graph for each statement, depicting the key message(s) implied by each statement WFP Markets Learning Programme Price Analysis Training

Marketastan 2.1.b. Debriefing 1.Northern HHs food expenses 2.Wheat price trends by province 3.Seasonal patterns of wheat prices 4.Real wage trend 5.Food insecurity by livelihood group WFP Markets Learning Programme Price Analysis Training

Wrap-up: Graphical Analysis Data Quality  Review & clean data first: then decide how you will deal with missing data Presentation:  Image should clarify the message – not require additional effort by the user to understand what you are presenting  …and remember: keep it simple, please! WFP Markets Learning Programme Price Analysis Training