diff --git a/.claude/settings.local.json b/.claude/settings.local.json
new file mode 100644
index 000000000..d56093d80
--- /dev/null
+++ b/.claude/settings.local.json
@@ -0,0 +1,17 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(xargs -I {} wc -l {})",
+      "Bash(mvn clean *)",
+      "Bash(python -c \"import docx; print\\('python-docx available'\\)\")",
+      "Bash(python3 -c \"import docx; print\\('ok'\\)\")",
+      "Bash(where py *)",
+      "Bash(py --version)",
+      "Bash(py -c \"import docx; print\\('ok'\\)\")",
+      "Bash(py -m pip install python-docx -q)",
+      "Bash(py generate_review.py)",
+      "Bash(pip show *)",
+      "PowerShell(Get-Command *)"
+    ]
+  }
+}
diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 000000000..43891ca9c
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1,121 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Important: Directory Path Contains Spaces
+
+The project root is `C:\MyFiles\99 DEV ENV\JAS-MINE\SimPaths`. The path contains spaces, so always wrap paths in double quotes in shell/Bash commands, e.g.:
+
+```bash
+cd "C:\MyFiles\99 DEV ENV\JAS-MINE\SimPaths"
+mvn -f "C:\MyFiles\99 DEV ENV\JAS-MINE\SimPaths\pom.xml" compile
+```
+
+## Build & Run Commands
+
+```bash
+# Compile only
+mvn compile
+
+# Run unit tests (excludes integration tests)
+mvn test
+
+# Run a single test class
+mvn test -Dtest=MahalanobisDistanceTest
+
+# Run a single test method
+mvn test -Dtest=PersonTest#methodName
+
+# Run integration tests (requires pre-built JARs)
+mvn failsafe:integration-test
+
+# Build shaded JARs (produces singlerun.jar and multirun.jar in project root)
+mvn package
+
+# Run simulation headless via multirun.jar (uses config/default.yml)
+java -jar multirun.jar -config config/default.yml
+
+# Run database setup only
+java -jar multirun.jar -DBSetup -config config/default.yml
+
+# Run with GUI (single run)
+java -jar singlerun.jar
+```
+
+Java 19 is required (configured in pom.xml). Dependencies are pulled from Maven Central and JitPack (for JAS-mine).
+
+## Architecture Overview
+
+SimPaths is a **dynamic microsimulation model** built on the [JAS-mine](https://github.com/jasmineRepo) simulation framework. It projects individual and household life histories year-by-year across domains: labour market, health, demographics, social care, and taxes/benefits.
+
+### Simulation entity hierarchy
+
+```
+Household          — groups BenefitUnits sharing a dwelling (parent–adult-child links)
+  └─ BenefitUnit  — the tax/benefit assessment unit (couple or single + dependent children)
+       └─ Person  — the individual agent (all life-course state is stored here)
+```
+
+All three are JPA `@Entity` classes persisted via Hibernate/H2. Each carries a `PanelEntityKey` (id + simulation_time + simulation_run).
+
+### Simulation lifecycle
+
+`SimPathsModel` (extends `AbstractSimulationManager`) owns the main simulation loop. Each year it fires ordered events that update entities via `EventListener.onEvent()`. The sequence covers: mortality → union formation/dissolution → fertility → education → labour market → taxes/benefits → health → social care → statistics collection.
+
+### Key classes to know
+
+| Class | Role |
+|---|---|
+| `SimPathsModel` | Orchestrates yearly event schedule; holds all population lists |
+| `SimPathsStart` | Entry point for single runs (GUI or headless) |
+| `SimPathsMultiRun` | Entry point for multi-run / sensitivity analysis |
+| `SimPathsCollector` | Collects and exports output statistics each year |
+| `Parameters` | Static store for all model parameters and regression coefficients loaded from Excel |
+| `ManagerRegressions` | Routes regression evaluation calls to the correct JAS-mine regression objects |
+| `Person` / `BenefitUnit` | Core simulation agents — most behavioural logic lives here |
+
+### Tax-benefit imputation (`model/taxes/`)
+
+Tax and benefit outcomes are not calculated analytically. Instead, the model uses **statistical matching**: simulated households are matched to a pre-built donor database derived from EUROMOD/UKMOD output. `TaxDonorDataParser` builds this database; `DonorTaxImputation` performs the matching using a nearest-neighbour key function (`KeyFunction1`–`KeyFunction4`).
+
+### Intertemporal optimisation (`model/decisions/`)
+
+An optional backward-induction module solves for optimal lifetime consumption and labour supply. `ManagerSolveGrids` runs the solution over a multi-dimensional state-space grid (age, health, education, pension, region, etc.). `ManagerPopulateGrids` sets up the grid geometry. This is computationally expensive and disabled by default (`enableIntertemporalOptimisations: false`).
+
+### Regression system
+
+All behavioural equations are estimated externally and loaded at startup from Excel files in `input/`. `Parameters` loads them via JAS-mine's `ExcelAssistant`/`MultiKeyCoefficientMap`. `RegressionName` (enum) names every equation; `ManagerRegressions` dispatches calls by type (linear, probit, ordered probit, multinomial logit, etc.).
+
+### Alignment
+
+Several demographic processes are aligned to external targets (ONS projections, LFS shares) via `ActivityAlignmentV2`, `FertilityAlignment`, `PartnershipAlignment`, `InSchoolAlignment`, `SocialCareAlignment`. Alignment factors are exported to `AlignmentAdjustmentFactors1.csv` each run.
+
+### Configuration
+
+Runs are configured via YAML files in `config/`. `default.yml` documents all available keys with their defaults. CLI flags override YAML values. `SimPathsMultiRun` reads the YAML and reflectively sets fields on `SimPathsModel`, `SimPathsCollector`, and `Parameters`.
+
+### Output
+
+Output is written to `output/<run-timestamp>/csv/` by `SimPathsCollector`. Key files:
+- `Statistics1.csv` — income distribution (Gini, percentiles, S-Index)
+- `Statistics2.csv` — demographic validation (partnership, employment, health by age/gender)
+- `EmploymentStatistics.csv`, `HealthStatistics.csv` — domain-specific time series
+- `AlignmentAdjustmentFactors1.csv` — alignment diagnostics
+
+### Integration tests
+
+`RunSimPathsIntegrationTest` runs the full simulation end-to-end using the built JARs and compares CSV output against reference files in `src/test/java/simpaths/integrationtest/expected/`. If a substantive change shifts the output, update the expected files and commit them.
+
+## Domain Knowledge
+
+This section records design principles and non-obvious rationale accumulated through development. Update it as new insights emerge.
+
+### Price levels: SimPaths vs. the tax donor database
+
+All SimPaths financial variables are stored in **real 2015 prices** (`BASE_PRICE_YEAR`). The tax donor database, however, is denominated in **nominal prices of the respective policy year**.
+
+Tax donor matching therefore requires a two-step price bridge:
+1. Inflate SimPaths income to policy-year prices before matching.
+2. Deflate the imputed financial values from the matched donor record back to 2015 prices.
+
+The default uprating series is `TimeSeriesVariable.Inflation`, sourced from the `UK_inflation` worksheet in `input/time_series_factor.xlsx`. An alternative option (added 2026-04) allows wage growth to be used instead of price growth for the initial matching step, controlled via a config flag.
\ No newline at end of file
diff --git a/config/default.yml b/config/default.yml
index 864ff0d2b..785e37cba 100644
--- a/config/default.yml
+++ b/config/default.yml
@@ -75,6 +75,11 @@ model_args:
   # --- Tax-benefit imputation ---
 #    donorPoolAveraging: true    # if true, average disposable income over k nearest-neighbour donors
                                  # rather than using the single closest donor; reduces imputation volatility
+#    taxDonorUpratingByWage: false  # if true, scale simulated income by nominal wage growth (compound of
+                                    # WageGrowth and Inflation indices). before matching to the tax donor
+                                    # database, instead of price growth only. Imputed financial flows are
+                                    # always deflated back to BASE_PRICE_YEAR (2015) using Inflation only,
+                                    # regardless of this setting.
 
   # --- Regression stochasticity ---
 #    addRegressionStochasticComponent: true   # include the residual draw in regression predictions
diff --git a/input/EUROMODoutput/training/DatabaseCountryYear.xlsx b/input/EUROMODoutput/training/DatabaseCountryYear.xlsx
index f6173d4ad..71e701416 100644
Binary files a/input/EUROMODoutput/training/DatabaseCountryYear.xlsx and b/input/EUROMODoutput/training/DatabaseCountryYear.xlsx differ
diff --git a/input/EUROMODpolicySchedule.xlsx b/input/EUROMODpolicySchedule.xlsx
index e19a0ca8d..2b162e6f2 100644
Binary files a/input/EUROMODpolicySchedule.xlsx and b/input/EUROMODpolicySchedule.xlsx differ
diff --git a/src/main/java/simpaths/data/Parameters.java b/src/main/java/simpaths/data/Parameters.java
index 114eb468c..4d249ca3b 100644
--- a/src/main/java/simpaths/data/Parameters.java
+++ b/src/main/java/simpaths/data/Parameters.java
@@ -879,6 +879,7 @@ else if(numberOfChildren <= 5) {
     public static boolean flagSuppressChildcareCosts;
     public static boolean flagSuppressSocialCareCosts;
     public static boolean donorPoolAveraging;
+    public static boolean taxDonorUpratingByWage;
     public static boolean lifetimeIncomeImpute;
 
     public static double realInterestRateInnov;
@@ -908,10 +909,11 @@ private static void addFixedCostRegressors(MultiKeyCoefficientMap map, List<Stri
      */
     public static void loadParameters(Country country, int maxAgeModel, boolean enableIntertemporalOptimisations,
                                       boolean projectFormalChildcare, boolean projectSocialCare, boolean donorPoolAveraging1,
-                                      boolean fixTimeTrend, boolean defaultToTimeSeriesAverages, boolean taxDBMatches,
-                                      Integer timeTrendStops, int startYearModel, int endYearModel, double interestRateInnov1,
-                                      double disposableIncomeFromLabourInnov1, boolean flagSuppressChildcareCosts1,
-                                      boolean flagSuppressSocialCareCosts1, boolean lifetimeIncomeImpute1) {
+                                      boolean taxDonorUpratingByWage1, boolean fixTimeTrend, boolean defaultToTimeSeriesAverages,
+                                      boolean taxDBMatches, Integer timeTrendStops, int startYearModel, int endYearModel,
+                                      double interestRateInnov1, double disposableIncomeFromLabourInnov1,
+                                      boolean flagSuppressChildcareCosts1, boolean flagSuppressSocialCareCosts1,
+                                      boolean lifetimeIncomeImpute1) {
 
         // display a dialog box to let the user know what is happening
         System.out.println("Loading model parameters");
@@ -942,6 +944,7 @@ public static void loadParameters(Country country, int maxAgeModel, boolean enab
         flagSuppressChildcareCosts = flagSuppressChildcareCosts1;
         flagSuppressSocialCareCosts = flagSuppressSocialCareCosts1;
         donorPoolAveraging = donorPoolAveraging1;
+        taxDonorUpratingByWage = taxDonorUpratingByWage1;
         realInterestRateInnov = interestRateInnov1;
         disposableIncomeFromLabourInnov = disposableIncomeFromLabourInnov1;
         lifetimeIncomeImpute = lifetimeIncomeImpute1;
@@ -3057,11 +3060,25 @@ public static MahalanobisDistance getMdDualIncomeChildcare() {
     public static double normaliseWeeklyIncome(int priceYear, double weeklyFinancial) {
         return normaliseMonthlyIncome(priceYear, weeklyFinancial * WEEKS_PER_MONTH);
     }
-    public static double normaliseMonthlyIncome(int priceYear, double monthlyFinancial) {
+    public static double normaliseWeeklyIncome(int currentPriceYear, int targetWagesYear, double weeklyFinancial) {
+        return normaliseMonthlyIncome(currentPriceYear, targetWagesYear, weeklyFinancial * WEEKS_PER_MONTH);
+    }
+    public static double normaliseMonthlyIncome(int currentPriceYear, double monthlyFinancial) {
+        return normaliseMonthlyIncome(currentPriceYear, BASE_PRICE_YEAR, currentPriceYear, currentPriceYear, monthlyFinancial);
+    }
+    public static double normaliseMonthlyIncome(int currentPriceYear, int targetWagesYear, double monthlyFinancial) {
+        return normaliseMonthlyIncome(currentPriceYear, BASE_PRICE_YEAR, currentPriceYear, targetWagesYear, monthlyFinancial);
+    }
+    public static double normaliseWeeklyIncome(int currentPriceYear, int targetPriceYear, int currentWagesYear, int targetWagesYear, double weeklyFinancial) {
+        return normaliseMonthlyIncome(currentPriceYear, targetPriceYear, currentWagesYear, targetWagesYear, weeklyFinancial * WEEKS_PER_MONTH);
+    }
+    public static double normaliseMonthlyIncome(int currentPriceYear, int targetPriceYear, int currentWagesYear, int targetWagesYear, double monthlyFinancial) {
         double infAdj = 1.0;
-        if (priceYear != BASE_PRICE_YEAR)
-            infAdj = getTimeSeriesValue(BASE_PRICE_YEAR, TimeSeriesVariable.Inflation) / getTimeSeriesValue(priceYear, TimeSeriesVariable.Inflation);
-        return Parameters.asinh(monthlyFinancial * infAdj);
+        if (currentPriceYear != targetPriceYear)
+            infAdj = getTimeSeriesValue(targetPriceYear, TimeSeriesVariable.Inflation) / getTimeSeriesValue(currentPriceYear, TimeSeriesVariable.Inflation);
+        if (currentWagesYear != targetWagesYear)
+            infAdj *= getTimeSeriesValue(targetWagesYear, TimeSeriesVariable.WageGrowth) / getTimeSeriesValue(currentWagesYear, TimeSeriesVariable.WageGrowth);
+        return asinh(monthlyFinancial * infAdj);
     }
     public static void setTrainingFlag(boolean flag) {
         trainingFlag = flag;
diff --git a/src/main/java/simpaths/model/Person.java b/src/main/java/simpaths/model/Person.java
index 3f895c713..fb66cab17 100644
--- a/src/main/java/simpaths/model/Person.java
+++ b/src/main/java/simpaths/model/Person.java
@@ -1466,8 +1466,9 @@ protected void evaluateSocialCareReceipt() {
             double recCareInnov = statInnovations.getDoubleDraw(7);
             double probNeedCare = Parameters.getRegNeedCareS2a().getProbability(this, Person.DoublesVariables.class);
             if (recCareInnov < probNeedCare) {
-                // need care
                 careNeedFlag = Indicator.True;
+            } else {
+                careNeedFlag = Indicator.False;
             }
 
             double probRecCare = Parameters.getRegReceiveCareS2b().getProbability(this, Person.DoublesVariables.class);
diff --git a/src/main/java/simpaths/model/SimPathsModel.java b/src/main/java/simpaths/model/SimPathsModel.java
index 7939ca560..5554683b0 100644
--- a/src/main/java/simpaths/model/SimPathsModel.java
+++ b/src/main/java/simpaths/model/SimPathsModel.java
@@ -204,6 +204,9 @@ public void setFirstRun(boolean firstRun) {
     @GUIparameter(description = "Average over donor pool when imputing transfer payments")
     public boolean donorPoolAveraging = true;
 
+    @GUIparameter(description = "Scale simulated income by wage growth when imputing taxes and benefits")
+    public boolean taxDonorUpratingByWage = false;
+
     private int ordering = Parameters.MODEL_ORDERING;    //Used in Scheduling of model events.  Schedule model events at the same time as the collector and observer events, but a lower order, so will be fired before the collector and observer have updated.
 
     private Set<Person> persons;
@@ -380,9 +383,9 @@ public void buildObjects() {
 
         // load model parameters
         Parameters.loadParameters(country, maxAge, enableIntertemporalOptimisations, projectFormalChildcare,
-                projectSocialCare, donorPoolAveraging, fixTimeTrend, flagDefaultToTimeSeriesAverages, saveImperfectTaxDBMatches,
-                timeTrendStopsIn, startYear, endYear, interestRateInnov, disposableIncomeFromLabourInnov, flagSuppressChildcareCosts,
-                flagSuppressSocialCareCosts, lifetimeIncomeImpute);
+                projectSocialCare, donorPoolAveraging, taxDonorUpratingByWage, fixTimeTrend, flagDefaultToTimeSeriesAverages,
+                saveImperfectTaxDBMatches, timeTrendStopsIn, startYear, endYear, interestRateInnov,
+                disposableIncomeFromLabourInnov, flagSuppressChildcareCosts, flagSuppressSocialCareCosts, lifetimeIncomeImpute);
         if (lifetimeIncomeGenerate) {
             ManagerProjectLifetimeIncomes.run(log, lifetimeIncomeStartBirthYear,
                     lifetimeIncomeEndBirthYear, lifetimeIncomeEndAge, lifetimeIncomeCohortSize, lifetimeIncomeWriteToCSV,
@@ -722,6 +725,8 @@ private void saveRunParameters() {
             pw.println(line);
             line = "donorPoolAveraging: " + donorPoolAveraging;
             pw.println(line);
+            line = "taxDonorUpratingByWage: " + taxDonorUpratingByWage;
+            pw.println(line);
             line = "initialisePotentialEarningsFromDatabase: " + initialisePotentialEarningsFromDatabase;
             pw.println(line);
             line = "useWeights: " + useWeights;
@@ -2928,6 +2933,8 @@ public void setCountry(Country country) {
     public void setProjectFormalChildcare(boolean projectFormalChildcare) { this.projectFormalChildcare = projectFormalChildcare; }
     public boolean getDonorPoolAveraging() { return donorPoolAveraging; }
     public void setDonorPoolAveraging(boolean val) { donorPoolAveraging = val; }
+    public boolean getTaxDonorUpratingByWage() { return taxDonorUpratingByWage; }
+    public void setTaxDonorUpratingByWage(boolean val) { taxDonorUpratingByWage = val; }
 
     public Integer getPopSize() {
         return popSize;
diff --git a/src/main/java/simpaths/model/taxes/DonorTaxImputation.java b/src/main/java/simpaths/model/taxes/DonorTaxImputation.java
index d0aa8edd1..2b67b503e 100644
--- a/src/main/java/simpaths/model/taxes/DonorTaxImputation.java
+++ b/src/main/java/simpaths/model/taxes/DonorTaxImputation.java
@@ -3,6 +3,7 @@
 
 import microsim.engine.SimulationEngine;
 import org.apache.commons.lang3.tuple.Triple;
+import simpaths.model.enums.TimeSeriesVariable;
 import simpaths.model.enums.UpratingCase;
 
 import java.util.*;
@@ -153,21 +154,25 @@ public void evaluate() {
         // The candidate pool is organised in increasing order of original income
         // ordering is controlled by database query in SimPathsModel.populateTaxdbReferences
         // normalised income is monthly in BASE_PRICE_YEAR prices (same as EUROMOD)
+        // Search here uses the golden search algorithm
         targetNormalisedOriginalIncome = Parameters.normaliseWeeklyIncome(keys.getPriceYear(), keys.getOriginalIncomePerWeek());
         int lowerInd, upperInd, testInd;
         double lowerOrigInc, upperOrigInc, testOrigInc;
         final double MEAN_BIAS = 0.5;
+        int targetWagesYear = (Parameters.taxDonorUpratingByWage) ? keys.getSimYear() : systemYear;
 
         lowerInd = 0;
-        lowerOrigInc = Parameters.getDonorPool().get(candidatePool.get(lowerInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth();
+        lowerOrigInc = Parameters.getDonorPool().get(candidatePool.get(lowerInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth(targetWagesYear);
         upperInd = candidatePool.size()-1;
-        upperOrigInc = Parameters.getDonorPool().get(candidatePool.get(upperInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth();
+        upperOrigInc = Parameters.getDonorPool().get(candidatePool.get(upperInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth(targetWagesYear);
 
-        int iiTarget;
-        if (targetNormalisedOriginalIncome<lowerOrigInc) {
+        int iiTarget, iiNearest;
+        if (targetNormalisedOriginalIncome < lowerOrigInc) {
             iiTarget = lowerInd;
-        } else if (targetNormalisedOriginalIncome>upperOrigInc) {
+            iiNearest = lowerInd;
+        } else if (targetNormalisedOriginalIncome > upperOrigInc) {
             iiTarget = upperInd;
+            iiNearest = upperInd;
         } else {
 
             while (upperInd > lowerInd+1) {
@@ -175,8 +180,7 @@ public void evaluate() {
                 double adjFactor = 0.5 * MEAN_BIAS + (targetNormalisedOriginalIncome-lowerOrigInc) / (upperOrigInc - lowerOrigInc) * (1-MEAN_BIAS);
                 int adjInd = (int) ((upperInd - lowerInd) * adjFactor);
                 testInd = lowerInd + Math.max(1, adjInd);
-                testOrigInc = Parameters.getDonorPool().get(candidatePool.get(testInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth();
-
+                testOrigInc = Parameters.getDonorPool().get(candidatePool.get(testInd)).getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth(targetWagesYear);
                 if (testOrigInc > targetNormalisedOriginalIncome) {
                     upperInd = testInd;
                     upperOrigInc = testOrigInc;
@@ -190,11 +194,16 @@ public void evaluate() {
                 }
             }
             iiTarget = upperInd;
+            if (Math.abs(upperOrigInc-targetNormalisedOriginalIncome) < Math.abs(lowerOrigInc-targetNormalisedOriginalIncome)) {
+                iiNearest = upperInd;
+            } else {
+                iiNearest = lowerInd;
+            }
         }
-        DonorTaxUnit targetCandidate = Parameters.getDonorPool().get(candidatePool.get(iiTarget));
+        // note that actual donor is identified by focussed search below
+        DonorTaxUnit targetCandidate = Parameters.getDonorPool().get(candidatePool.get(iiNearest));
         donorID = targetCandidate.getId();
-        double targetIncomeDifference = Math.abs(targetNormalisedOriginalIncome -
-                targetCandidate.getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth());
+        double targetIncomeDifference = Math.abs(targetNormalisedOriginalIncome - targetCandidate.getPolicyBySystemYear(systemYear).getNormalisedOriginalIncomePerMonth(targetWagesYear));
         if (!keys.isLowIncome(matchRegime)) {
             targetIncomeDifference /= Math.abs(targetNormalisedOriginalIncome);
             targetIncomeDifference *= 100;
@@ -206,16 +215,14 @@ public void evaluate() {
         // focussed search around target
         //------------------------------------------------------------
         List<CandidateList> candidatesList = new ArrayList<>();
-        int bracketPts = (!flagChildcareCost && !flagSecondIncome) ? 2 : 60;
-        double oi = keys.getOriginalIncomePerWeek();
-        double si = keys.getSecondIncomePerWeek();
-        double cc = keys.getChildcareCostPerWeek();
-        double[] targetVector = getMeasurementVector(keys.getPriceYear(), oi, flagSecondIncome, si, flagChildcareCost, cc);
+        int bracketPts = (!flagChildcareCost && !flagSecondIncome) ? 2 : 50;
+        double[] targetVector = getMeasurementVector(keys.getPriceYear(), Parameters.BASE_PRICE_YEAR, keys.getSimYear(), keys.getSimYear(),
+                keys.getOriginalIncomePerWeek(), flagSecondIncome, keys.getSecondIncomePerWeek(), flagChildcareCost, keys.getChildcareCostPerWeek());
         for (int increment=-1; increment<2; increment=increment+2) {
             // search backward and then forward through candidate list
 
             // initialise directional search
-            int bracketInd = 0;
+            int bracketInd = 0; // number of consecutive points within bracket
             double localMin = 999.0;
             double bracketDist = -999.0;
             int ii;
@@ -227,17 +234,20 @@ public void evaluate() {
             while (ii>=0 && ii<candidatePool.size()) {
 
                 DonorTaxUnit candidate = Parameters.getDonorPool().get(candidatePool.get(ii));
-                double[] candidateVector = getCandidateMeasVector(candidate, flagSecondIncome, flagChildcareCost);
+                double[] candidateVector = getCandidateMeasVector(systemYear, Parameters.BASE_PRICE_YEAR, systemYear, targetWagesYear,
+                        candidate, flagSecondIncome, flagChildcareCost);
                 double distance = evaluateDistance(targetVector, candidateVector, flagSecondIncome, flagChildcareCost);
                 if (Math.abs(distance - bracketDist) > 1.0E-4) {
                     bracketDist = distance;
                     bracketInd++;
                 }
                 if (distance < localMin) {
+                    // new minimum found: reset bracket
                     bracketInd = 0;
                     localMin = distance;
                 }
                 if (bracketInd <= bracketPts) {
+                    // add candidate to list
                     candidatesList.add(new CandidateList(candidate, candidate.getWeight(), distance));
                 } else {
                     break;
@@ -247,7 +257,7 @@ public void evaluate() {
         }
 
         // select subset of preferred candidates
-        Collections.sort(candidatesList, new CandidateListComparator());
+        candidatesList.sort(new CandidateListComparator());
         int candidateLast = 0;
         int bracketInd = 0;
         double bracketDist = -999.0;
@@ -270,7 +280,7 @@ public void evaluate() {
 
         // If focussed search produced no candidates, fall back to nearest neighbour.
         if (candidatesList.isEmpty()) {
-            DonorTaxUnit candidate = Parameters.getDonorPool().get(candidatePool.get(iiTarget));
+            DonorTaxUnit candidate = Parameters.getDonorPool().get(candidatePool.get(iiNearest));
             candidatesList.add(new CandidateList(candidate, candidate.getWeight(), 0.0));
             weightSum = candidate.getWeight();
         }
@@ -294,7 +304,11 @@ public void evaluate() {
         setReceivedUC(0);
         setReceivedLegacyBenefit(0);
         if (systemYear != keys.getPriceYear())
-            infAdj = Parameters.getTimeSeriesIndex(keys.getPriceYear(), UpratingCase.TaxDonor) / Parameters.getTimeSeriesIndex(systemYear, UpratingCase.TaxDonor);
+            infAdj = Parameters.getTimeSeriesValue(keys.getPriceYear(), TimeSeriesVariable.Inflation) /
+                    Parameters.getTimeSeriesValue(systemYear, TimeSeriesVariable.Inflation);
+        if (systemYear != keys.getSimYear() && Parameters.taxDonorUpratingByWage)
+            infAdj = infAdj * Parameters.getTimeSeriesValue(keys.getSimYear(), TimeSeriesVariable.WageGrowth) /
+                    Parameters.getTimeSeriesValue(systemYear, TimeSeriesVariable.WageGrowth);
         for (CandidateList candidateList : candidatesList) {
             // loop over each preferred candidate
 
@@ -332,30 +346,26 @@ public void evaluate() {
         }
         if (Math.abs(disposableIncomePerWeek+999.0)<1.0E-5) {
             // Deterministic fallback: use nearest neighbour directly.
-            DonorTaxUnit fallback = (targetCandidate != null) ? targetCandidate :
-                    (!candidatesList.isEmpty() ? candidatesList.get(0).getCandidate() : null);
-            if (fallback != null) {
-                donorID = fallback.getId();
-                if (keys.isLowIncome(matchRegime)) {
-                    disposableIncomePerWeek = fallback.getPolicyBySystemYear(systemYear).getDisposableIncomePerMonth()
-                            / Parameters.WEEKS_PER_MONTH * infAdj;
-                    benefitsReceivedPerWeek = (fallback.getPolicyBySystemYear(systemYear).getBenMeansTestPerMonth()
-                            + fallback.getPolicyBySystemYear(systemYear).getBenNonMeansTestPerMonth())
-                            / Parameters.WEEKS_PER_MONTH * infAdj;
+            donorID = targetCandidate.getId();
+            if (keys.isLowIncome(matchRegime)) {
+                disposableIncomePerWeek = targetCandidate.getPolicyBySystemYear(systemYear).getDisposableIncomePerMonth()
+                        / Parameters.WEEKS_PER_MONTH * infAdj;
+                benefitsReceivedPerWeek = (targetCandidate.getPolicyBySystemYear(systemYear).getBenMeansTestPerMonth()
+                        + targetCandidate.getPolicyBySystemYear(systemYear).getBenNonMeansTestPerMonth())
+                        / Parameters.WEEKS_PER_MONTH * infAdj;
+            } else {
+                double origIncMonth = targetCandidate.getPolicyBySystemYear(systemYear).getOriginalIncomePerMonth();
+                if (Math.abs(origIncMonth) > 1.0E-9) {
+                    disposableIncomePerWeek = targetCandidate.getPolicyBySystemYear(systemYear).getDisposableIncomePerMonth() / origIncMonth;
+                    benefitsReceivedPerWeek = (targetCandidate.getPolicyBySystemYear(systemYear).getBenMeansTestPerMonth()
+                            + targetCandidate.getPolicyBySystemYear(systemYear).getBenNonMeansTestPerMonth()) / origIncMonth;
                 } else {
-                    double origIncMonth = fallback.getPolicyBySystemYear(systemYear).getOriginalIncomePerMonth();
-                    if (Math.abs(origIncMonth) > 1.0E-9) {
-                        disposableIncomePerWeek = fallback.getPolicyBySystemYear(systemYear).getDisposableIncomePerMonth() / origIncMonth;
-                        benefitsReceivedPerWeek = (fallback.getPolicyBySystemYear(systemYear).getBenMeansTestPerMonth()
-                                + fallback.getPolicyBySystemYear(systemYear).getBenNonMeansTestPerMonth()) / origIncMonth;
-                    } else {
-                        disposableIncomePerWeek = 0.0;
-                        benefitsReceivedPerWeek = 0.0;
-                    }
+                    disposableIncomePerWeek = 0.0;
+                    benefitsReceivedPerWeek = 0.0;
                 }
-                setReceivedUC(fallback.getPolicyBySystemYear(systemYear).getReceivesUC());
-                setReceivedLegacyBenefit(fallback.getPolicyBySystemYear(systemYear).getReceivesLegacyBenefit());
             }
+            setReceivedUC(targetCandidate.getPolicyBySystemYear(systemYear).getReceivesUC());
+            setReceivedLegacyBenefit(targetCandidate.getPolicyBySystemYear(systemYear).getReceivesLegacyBenefit());
         }
         if (Math.abs(disposableIncomePerWeek+999.0)<1.0E-5)
             throw new RuntimeException("Failed to populate disposable income and benefits from donor with inner key value " + keys.getKey(0));
@@ -425,33 +435,51 @@ public static int getCounterVal(MatchFeature targetFeature, int regime, int inde
         throw new RuntimeException("attempt to evaluate index of unrecognised target feature");
     }
 
-    private double[] getMeasurementVector(int priceYear, double originalIncomePerWeek, boolean flagSecondIncome, double secondIncomePerWeek,
-                                          boolean flagChildcareCost, double childcareCostPerWeek) {
-
-        double oiAdj = Parameters.normaliseWeeklyIncome(priceYear, originalIncomePerWeek);
-        double siAdj = Parameters.normaliseWeeklyIncome(priceYear, secondIncomePerWeek);
-        double ccAdj = Parameters.normaliseWeeklyIncome(priceYear, childcareCostPerWeek);
+    /**
+     * Method to package array of metrics used to compare target against potential donors
+     *
+     * @param targetPriceYear           inflation year that monetary variables should be measured in
+     * @param currentPriceYear          inflation year that monetary variables currently measured in
+     * @param targetWagesYear           wage growth year that monetary variables should be measured in
+     * @param currentWagesYear          wage growth year that monetary variables currently measured in
+     * @param originalIncomePerWeek     current original income (per week)
+     * @param flagSecondIncome          if true, second income is also measured
+     * @param secondIncomePerWeek       second income (per week, if measured)
+     * @param flagChildcareCost         if true, childcare cost is also measured
+     * @param childcareCostPerWeek      childcare cost (per week, if measured)
+     * @return
+     */
+    private double[] getMeasurementVector(int currentPriceYear, int targetPriceYear,
+                                          int currentWagesYear, int targetWagesYear,
+                                          double originalIncomePerWeek, boolean flagSecondIncome,
+                                          double secondIncomePerWeek, boolean flagChildcareCost, double childcareCostPerWeek) {
+
+        double oiAdj = Parameters.normaliseWeeklyIncome(currentPriceYear, targetPriceYear, currentWagesYear, targetWagesYear, originalIncomePerWeek);
+        double siAdj = Parameters.normaliseWeeklyIncome(currentPriceYear, targetPriceYear, currentWagesYear, targetWagesYear, secondIncomePerWeek);
+        double ccAdj = Parameters.normaliseWeeklyIncome(currentPriceYear, targetPriceYear, currentWagesYear, targetWagesYear, childcareCostPerWeek);
         if (!flagSecondIncome && !flagChildcareCost) {
             return new double[] {oiAdj};
         } else if (flagSecondIncome && !flagChildcareCost) {
             return new double[] {oiAdj, siAdj};
-        } else if (!flagSecondIncome && flagChildcareCost) {
+        } else if (!flagSecondIncome) {
             return new double[]{oiAdj, ccAdj};
         } else {
             return new double[]{oiAdj, siAdj, ccAdj};
         }
     }
-    private double[] getCandidateMeasVector(DonorTaxUnit candidate, boolean flagSecondIncome, boolean flagChildcareCost) {
+    private double[] getCandidateMeasVector(int currentPriceYear, int targetPriceYear,
+                                            int currentWagesYear, int targetWagesYear,
+                                            DonorTaxUnit candidate, boolean flagSecondIncome, boolean flagChildcareCost) {
 
-        int priceYear = Parameters.BASE_PRICE_YEAR;
-        double oiWeekly = candidate.getPolicyBySystemYear(priceYear).getOriginalIncomePerMonth() / Parameters.WEEKS_PER_MONTH;
+        double oiWeekly = candidate.getPolicyBySystemYear(currentPriceYear).getOriginalIncomePerMonth() / Parameters.WEEKS_PER_MONTH;
         double siWeekly = 0.0;
         if (flagSecondIncome)
-            siWeekly = candidate.getPolicyBySystemYear(priceYear).getSecondIncomePerMonth() / Parameters.WEEKS_PER_MONTH;
+            siWeekly = candidate.getPolicyBySystemYear(currentPriceYear).getSecondIncomePerMonth() / Parameters.WEEKS_PER_MONTH;
         double ccWeekly = 0.0;
         if (flagChildcareCost)
-            ccWeekly = candidate.getPolicyBySystemYear(priceYear).getChildcareCostPerMonth() / Parameters.WEEKS_PER_MONTH;
-        return getMeasurementVector(priceYear, oiWeekly, flagSecondIncome, siWeekly, flagChildcareCost, ccWeekly);
+            ccWeekly = candidate.getPolicyBySystemYear(currentPriceYear).getChildcareCostPerMonth() / Parameters.WEEKS_PER_MONTH;
+        return getMeasurementVector(currentPriceYear, targetPriceYear, currentWagesYear, targetWagesYear,
+                oiWeekly, flagSecondIncome, siWeekly, flagChildcareCost, ccWeekly);
     }
     private double evaluateDistance(double[] targetVector, double[] candidateVector, boolean flagSecondIncome, boolean flagChildcareCost) {
         if (flagSecondIncome && flagChildcareCost) {
diff --git a/src/main/java/simpaths/model/taxes/DonorTaxUnitPolicy.java b/src/main/java/simpaths/model/taxes/DonorTaxUnitPolicy.java
index 359458e77..6c3d33e1e 100644
--- a/src/main/java/simpaths/model/taxes/DonorTaxUnitPolicy.java
+++ b/src/main/java/simpaths/model/taxes/DonorTaxUnitPolicy.java
@@ -91,6 +91,9 @@ public double getOriginalIncomePerMonth() {
             throw new RuntimeException("attempt to get original income before instantiated");
         return originalIncomePerMonth;
     }
+    public double getNormalisedOriginalIncomePerMonth(int targetWagesYear) {
+        return Parameters.normaliseMonthlyIncome(systemYear, targetWagesYear, getOriginalIncomePerMonth());
+    }
     public double getNormalisedOriginalIncomePerMonth() {
         return Parameters.normaliseMonthlyIncome(systemYear, getOriginalIncomePerMonth());
     }
diff --git a/src/main/java/simpaths/model/taxes/TestTaxRoutine.java b/src/main/java/simpaths/model/taxes/TestTaxRoutine.java
index c5ccc29cd..6da90a8a3 100644
--- a/src/main/java/simpaths/model/taxes/TestTaxRoutine.java
+++ b/src/main/java/simpaths/model/taxes/TestTaxRoutine.java
@@ -23,9 +23,9 @@ public static void run() {
         // disability1/2: 0, 1
         // income: <946.17 <=2985.70, >2985.70
 
-        year = 2025;
-        age = 78;
-        adults = 2;
+        year = 2040;
+        age = 80;
+        adults = 1;
         children04 = 0;
         children59 = 0;
         children1017 = 0;
@@ -33,8 +33,8 @@ public static void run() {
         hoursWork2 = 0.0;
         disability1 = 0;
         disability2 = 0;
-        careProvision = 1;
-        originalIncomePerMonth = 0.0;
+        careProvision = 0;
+        originalIncomePerMonth = 23.75;
         secondIncomePerMonth = 0.0;
         childcarePerMonth = 0.0;
         evaluatedTransfers = new TaxEvaluation(year, age, adults, children04, children59, children1017, hoursWork1, hoursWork2, disability1, disability2, careProvision, originalIncomePerMonth, secondIncomePerMonth, childcarePerMonth, -2);
@@ -43,7 +43,7 @@ public static void run() {
         disposableIncomePerMonth = evaluatedTransfers.getDisposableIncomePerMonth();
         matchRegime = evaluatedTransfers.getImputedTransfers().getMatchCriterion();
 
-        year = 2025;
+        year = 2040;
         age = 48;
         adults = 2;
         children04 = 1;
@@ -63,7 +63,7 @@ public static void run() {
         disposableIncomePerMonth = evaluatedTransfers.getDisposableIncomePerMonth();
         matchRegime = evaluatedTransfers.getImputedTransfers().getMatchCriterion();
 
-        year = 2025;
+        year = 2040;
         age = 48;
         adults = 2;
         children04 = 0;
@@ -73,7 +73,7 @@ public static void run() {
         hoursWork2 = 0.0;
         disability1 = 1;
         disability2 = 0;
-        originalIncomePerMonth = 0.0;
+        originalIncomePerMonth = 2100.0;
         secondIncomePerMonth = 0.0;
         childcarePerMonth = 0.0;
         evaluatedTransfers = new TaxEvaluation(year, age, adults, children04, children59, children1017, hoursWork1, hoursWork2, disability1, disability2, careProvision, originalIncomePerMonth, secondIncomePerMonth, childcarePerMonth, -2);
@@ -82,7 +82,7 @@ public static void run() {
         disposableIncomePerMonth = evaluatedTransfers.getDisposableIncomePerMonth();
         matchRegime = evaluatedTransfers.getImputedTransfers().getMatchCriterion();
 
-        year = 2025;
+        year = 2040;
         age = 75;
         adults = 1;
         children04 = 0;
@@ -92,7 +92,7 @@ public static void run() {
         hoursWork2 = 0.0;
         disability1 = 1;
         disability2 = 0;
-        originalIncomePerMonth = 0.0;
+        originalIncomePerMonth = 200.0;
         secondIncomePerMonth = 0.0;
         childcarePerMonth = 0.0;
         evaluatedTransfers = new TaxEvaluation(year, age, adults, children04, children59, children1017, hoursWork1, hoursWork2, disability1, disability2, careProvision, originalIncomePerMonth, secondIncomePerMonth, childcarePerMonth, -2);
@@ -101,7 +101,7 @@ public static void run() {
         disposableIncomePerMonth = evaluatedTransfers.getDisposableIncomePerMonth();
         matchRegime = evaluatedTransfers.getImputedTransfers().getMatchCriterion();
 
-        year = 2025;
+        year = 2040;
         age = 57;
         adults = 1;
         children04 = 0;
@@ -109,7 +109,7 @@ public static void run() {
         children1017 = 0;
         hoursWork1 = 20.0;
         hoursWork2 = 0.0;
-        disability1 = 1;
+        disability1 = 0;
         disability2 = 0;
         originalIncomePerMonth = 4500.0;
         secondIncomePerMonth = 0.0;
@@ -120,7 +120,7 @@ public static void run() {
         disposableIncomePerMonth = evaluatedTransfers.getDisposableIncomePerMonth();
         matchRegime = evaluatedTransfers.getImputedTransfers().getMatchCriterion();
 
-        year = 2025;
+        year = 2040;
         age = 57;
         adults = 1;
         children04 = 0;
@@ -130,7 +130,7 @@ public static void run() {
         hoursWork2 = 0.0;
         disability1 = 1;
         disability2 = 0;
-        originalIncomePerMonth = 0.0;
+        originalIncomePerMonth = 350.0;
         secondIncomePerMonth = 0.0;
         childcarePerMonth = 0.0;
         evaluatedTransfers = new TaxEvaluation(year, age, adults, children04, children59, children1017, hoursWork1, hoursWork2, disability1, disability2, careProvision, originalIncomePerMonth, secondIncomePerMonth, childcarePerMonth, -2);
diff --git a/src/main/java/simpaths/model/taxes/database/TaxDonorDataParser.java b/src/main/java/simpaths/model/taxes/database/TaxDonorDataParser.java
index 01ec0ae15..f422706fc 100644
--- a/src/main/java/simpaths/model/taxes/database/TaxDonorDataParser.java
+++ b/src/main/java/simpaths/model/taxes/database/TaxDonorDataParser.java
@@ -438,7 +438,6 @@ public static String stringAppender(Collection<String> strings) {
      * output .txt files, picking up the relevant columns for each EUROMOD policy scenario, that
      * will eventually be parsed into the JAS-mine input database.
      *
-     *
      */
     public static void constructAggregateTaxDonorPopulationCSVfile(Country country, boolean showGui) {